NISTIR 7883

Standardized Performance Testing 

Metrics for Optical Coordinate 

Measurement Systems

S.D. Phillips

http://dx.doi.org/10.6028/NIST.IR.7883
NISTIR 7883

Standardized Performance Testing 

Metrics for Optical Coordinate 

Measurement Systems

S.D. Phillips

Semiconductor and Dimensional Division

Physical Measurement Laboratory

http://dx.doi.org/10.6028/NIST.IR.7883

May 2013

U.S. Department of Commerce 

Rebecca Blank, Acting Secretary

National Institute of Standards and Technology 

Patrick D. Gallagher, Under Secretary of Commerce for Standards and Technology and Director 
Standardized Performance Testing Metrics for Optical Coordinate Measurement Systems 

S.D. Phillips 

National Institute of Standards and Technology 

Gaithersburg MD 20899

Abstract: Optical probing technology on coordinate measuring machines (CMMs) operates significantly 

differently from discrete point probing associated with tactile probing CMMs. Hence, manufacturers of 

this technology seek to use different testing artifacts for standardized performance testing. However, 

the standardized performance metrics which describe the CMM’s measurement accuracy need to be 

comparable to other CMMs regardless of the probing technology. This paper examines several different 

metrics that can be computed from the test results of CMMs with optical probes, and these metrics are 

compared for equivalency to the canonical results specified by the ISO 10360 series of standards used 

for tactile CMMs. A derivation is presented which motivates a more detailed computer simulation study 

of nine different metrics. Of these nine, two metrics involve easily observable quantities for optical 

probing systems and are considered equivalent to the canonical performance test value. 

Background: Coordinate measuring machines with tactile (i.e., contact) probing systems have a welldefined performance testing procedure codified in standards such as ISO 10360-2 [1] or its US 

counterpart ASME B89.4.10360.2 [2]. The three dimensional (3D) spatial measuring performance is 

specified by the MPE(E0)

1

value which is the maximum permissible error (MPE) of the “E0” parameter2; 

this describes the length measuring accuracy of the CMM. In these standards, the performance test 

procedures (and hence the meaning of the E value) are described in detail. The test includes 35 

different measurements of calibrated length standards, each repeated three times, for a total of 105 

observed length errors. There are several different formats in which the MPE specification can be 

stated. In this paper the MPE(E) specification is considered an upper bound for all possible length 

measurement errors (regardless of sign) for a CMM that is within its Original Equipment Manufacturer 

(OEM) specified performance, i.e., Max|E| ≤ MPE(E)

3

. Each length measurement is specified as the 

point-to-point length derived from a single point coordinate recorded at each end of the calibrated 

standard, where the end surfaces are planar and the normal vectors to the two end surfaces are 

diametrically opposite, e.g., a gage block. This is taken as the canonical form of the measurement and 

the associated Max|E| value (of the 105 measurements) as its canonical test result value. 

Over the last several years a plethora of new 3D CMMs have become available using various forms of 

optical probing technology; these include laser scanning systems, optical fringe projection systems, and 

X-ray computer tomography systems. In many applications these systems can perform the same 

 

1

 In the most recent ISO standards the notation is E0, MPE however for readability in this paper it is denoted MPE(E0).

2

 The subscript associated with the E value specifies the ram axis offset for the probing system; this offset depends 

on how the probe is mounted and is not of immediate concern for this paper so the subscript is not presented in 

the rest of this paper. 

3

 In this paper the MPE is considered a constant, but a length dependent MPE is also a valid means of specifying 

the maximum error, i.e., there could be a different MPE value for each length of the artifact under testing. 

1

1
measurements as tactile CMMs, and hence users are faced with complex decisions regarding the capital 

equipment purchase of this equipment and the measurement application of this technology. One goal 

of standardized performance specifications4 is to make this decision more rigorous by allowing 

meaningful accuracy comparisons between different competing products. Consequently, developing a 

measurement performance specification that is comparable across multiple technologies is highly 

desirable. 

Since optical probing systems are obviously noncontact, new standardized testing procedures are

needed to specify these systems. However, the testing results (and hence the associated MPE 

specification) need to be closely comparable to that of MPE(E) for tactile CMMs in the sense that similar 

MPE(E) specifications across different technologically based CMMs will yield similar dimensional 

measurement accuracy for the same standardized measurand. 

Tactile CMMs are typically tested in the canonical manner using calibrated artifacts such as gage blocks 

or step gages that have parallel planar opposing faces. While a direct comparison of tactile and optical 

measurement systems would involve measuring the same artifact in the same manner, optical CMM 

systems frequently have line of sight requirements that make traditional artifacts problematic. 

Additionally, tactile CMMs are designed to record discrete point coordinates and then move on to the 

next point location, while optical systems frequently record hundreds (or thousands) of points very 

rapidly within a single scan. Hence optical CMMs generally prefer extended targets such as the spheres 

on ball bars or ball plates because the spherical surface is observable from most orientations and the 

surface allows large numbers of points to be recorded. The terms bi-directional measurement and unidirectional measurement are used to refer to the detection of “size” errors. A ball bar measured in a 

center-to-center manner is a unidirectional measurement whereas if the ball bar measurement is the 

center-to-center length plus the sum of each sphere radius it is a bidirectional measurement because 

the measurement of sphere diameter is sensitive to detecting errors in the CMM’s “effective probe 

size”5; canonical testing artifacts such as gage blocks are measured in a bidirectional manner. 

For reasons of economy and convenience, standardization committees seek testing methodology 

alternatives to the canonical procedure; in particular, to allow the measurement of many points on 

spherical targets yet yield a test value that is comparable to the canonical E value result. Hence a form 

of “equivalent” testing metric is needed for the performance test results and the associated CMM 

accuracy specifications. 

In the CMM performance testing sense, equivalence means that the test result – which in the canonical 

procedure is the maximum observed error, regardless of sign, of 105 bi-directionally measured lengths, 

is approximately the same6

. Since the E value test result is primarily designed to assess CMM volumetric 

measurement capability, e.g., to detect CMM structurally induced errors, Standards Committees 

 

4

 Standardized specifications also lower costs for manufacturers by eliminating idiosyncratic user specified tests, 

and by aggregating economy of scale on testing artifacts and technician training. 

5

The term “effective” is used because even in the tactile probing case the proper stylus size may be different from 

its physical size to account for effects such as stylus bending; analogous effects also occur for optical probes. 

6

Test values from repeated “E” tests on the same CMM rarely yield the exactly same value. 

2

2
designate the location and orientation of the 35 calibrated lengths for each type of CMM7

 so that they 

appropriately capture these errors for the particular system under test. 

Performance Test Equivalency and Error Detection 

To employ the use of spherical artifacts in the E test, the effect on various error sources – as detected in 

individual point coordinates – is considered first from a loose but intuitive model; later the quantitative 

simulation results will provide firm numerical results. 

Consider a bi-directional measurement and a uni-directional measurement, as shown in Figure 1. The 

error sources associated with the length measurement can be classified into three categories: 

Long range systematic errors: Geometrical errors in the CMM structure, thermal errors, etc. 

Short range errors: repeatability problems, probing system errors such as anisotropic stylus bending 

and stylus out-of-roundness, short range scale errors, etc. 

“Size” errors: an incorrect “effective probe size” as used by the CMM in length measurements. 

Consider two measurements, one on a gage block in the canonical manner and one on a ball bar. Let 

the location of the two ends of the gage block be the same as the ball bar, i.e., the 3D coordinates of the 

sphere centers of the ball bar be the same as the coordinates of the gaging points of the gage block. Let 

the balls be small in the sense that they detect short range errors but are not sensitive to long range 

errors. Then the ball bar center-to-center distance will record the same long range errors as that of the 

canonical measurement. Hence the histogram of the long range errors -- shown schematically in the 

center of Figure 1 – will be the same for both cases. 

Figure 1: Gage block bi-directional measurement and ball bar uni-directional measurement 

Let the balls be measured with a sufficient point density during the scanning process that the short 

range errors are significantly muted, i.e., “averaged out,” hence these errors must be added back to 

obtain an equivalency with the canonical single point bi-directional measurement case. The short range 

errors for the canonical measurement are schematically shown above each stylus tip in Figure 1. 

 

7

 For example, AACMM test artifact positions might be different from that of a Cartesian CMM but the intent with 

regard to error assessment is the same. 

3

3
It is also obvious that an error in the probing system’s effective probe size directly adds in a one-to-one 

manner8 to the sum of short range and long range errors for each length measurement in the canonical 

procedure. However, the uni-directional sphere center to sphere center case is insensitive to detecting 

this error. Hence it is clear that the error in the effective probe size9

 must be added to the individual 

uni-directional length measurement.10

For each gage block measurement these three errors combine together to yield the observed error; this 

occurs for all 105 length measurements. It is useful to consider the 105 test measurements repeated a 

large number of times, each time yielding a slightly different histogram because both the long range and 

the short range errors are not perfectly repeatable and may also change with time. Similarly the size 

errors may change, e.g., due to probe requalification. The combination of all these histograms yields a 

distribution of values. Then the expected E test result would be the 105th order statistic from a sample 

of 105 absolute values from this distribution. 

For two different performance tests to be metrologically equivalent, they must detect the same error 

sources and have similar sensitivities to these error sources; e.g., if the short range errors are increased 

such that one performance test result value increases by X micrometers, then the value obtained from 

the other performance test should similarly increase. 

The long range errors are the same for both the gage block and the ball bar cases; hence this 

distribution is obtained directly for the observed ball bar center-to-center length errors. 

The CMM’s effective probe size error can be observed directly in the ball bar case if the balls are 

calibrated for diameter or alternatively from the size error observed in a calibrated test sphere 

measurement, e.g., the PS value obtained from the probe size test in [3, 4]. An upper bound on the PS

value can be estimated from the OEM specifications: MPE(PS). This error arithmetically adds to each 

individual long range error. However, since the sign of the largest long range error and that of the size 

error may be different, it does not necessarily follow that the same test result value is obtained from the 

arithmetic addition of the size error and the largest (regardless of sign) center-to-center length error; 

see Annex A for additional details. 

Since the short range errors have been mostly averaged out over the ball surfaces, they need to be 

included as follows. Consider selecting any position of the 105 canonical measurements (pick an 

element from the center-to-center error distribution), since the short range errors can be considered 

random, an element from their distribution at the right end and similarly at the left end. From a 

statistical viewpoint, since these are independent distributions, the variances will sum arithmetically; an 

estimate of the short range errors can be obtained from the ISO 10360-5 (or equivalent) sphere form 

test result, i.e., the PF value [3]. For CMMs with tactile probing systems the PF value is the range of 

residuals of a least-squares sphere fit of 25 discrete probing points located approximately uniformly 

 

8

 For example, each micrometer of effective probe size error results in one micrometer error in the reported gage 

length. 

9

 In Figure 1 this is the effective stylus tip size. 

10 Mathematically, there is a difference between adding the size error to an individual length measurement and 

adding it to the test result due to the use of order statistics in the determination of the test result; see Annex A. 

4

4
distributed on a hemisphere of a test sphere. For CMMs with optical probing systems a similar test has 

been proposed [4] where the 25 residuals of the sphere fit derived from 25 “representative points,” 

each obtained from a small (non-overlapping) area on the test sphere surface. 

Equivalent Test Result Calculations 

First consider the case where the mean of the long range, short range, and probe size errors are all zero 

and the distributions are all Gaussian. The distribution of the 105 length errors can be considered the 

convolution of the input error distributions; hence the length errors are Gaussian distributed with mean 

zero with variance Errors, this is just the sum of the variances of the input error distributions. Let  be 

the number of standard deviations of a Gaussian distribution to yield the 105th order statistic from a 

sample of 105 absolute value length errors; for Gaussian distributions  is about 2.8. Noting that the 

long range errors are captured in the center-to-center length measurement allows the replacement of 

LR with EUni 105. Also observing that since √ is about 3.9; and that this is about the number of 

standard deviations of short range errors which is expected11 to produce the reported form error using 

the ISO 25 point test, i.e., the PF value; combining these observations results in Equation (1). The 

usefulness of Equation (1) is that EUni 105 (the largest observed error regardless of sign in the center-tocenter length of a calibrated ball bar) and the PF value (the form test result from [3] or [4]) are readily 

available test result values which can be combined to yield the equivalent bi-directional test result. 

  √

 

 

  √ 

  √  (1) 

In general, the distribution for the canonical length measurement errors will be biased due to a 

combination of a bias in the long range errors, e.g., a global scale error in the CMM, or a bias arising 

from an effective probe size error. While the center-to-center length of a ball bar is sensitive to the bias 

in the long range errors, it is insensitive to the effective probe size error. Since EUni 105 is the largest 

observed error in the center-to-center distance, regardless of sign, this observed quantity will include 

the long range bias effect. To address the effective probe size error we note that the order statistic E105

associated with taking the maximum from 105 absolute values arising from a Gaussian distribution of 

mean μ and standard deviation , N[μ,], is bounded as shown in Equation (2), where  is the expected 

value of the 105th order statistic of a sample of 105 absolute values taken from a N[0,1] population; this 

is also the number of standard deviations from a N[0,] population needed to reach this order statistic. 

  (2) 

A good estimate of the effective probe size error is the PS value obtained from an ISO probe test such as 

[3] or [4]. Using this Equation (1) becomes: 

 √ 

 where denotes an approximate upper bound. (3) 

 

11 For a Gaussian distribution of short range errors with standard deviation , and using the default ISO 10360-5 

test sampling strategy, the expected form error is 3.7  and has a standard deviation of 0.7 . 

5

5
In some testing situations, the ball bar will have spheres calibrated for their diameter and this will detect 

the effective probe size error as an error in the ball diameters. Hence the length composed of the 

center-to-center length plus the radius of ball 1 and the radius of ball 2 (as computed from a least 

squares sphere fit) denoted: LUni + R1 + R2 is a useful quantity. Let EUni RR 105 denote the largest of these 

105 lengths regardless of sign; this quantity would be equivalent to the canonical measurement if the 

short range errors were zero. Assuming that the spheres are densely measured so that the short range 

errors average out, then accounting for the short range errors in a manner similar to Equation (1) yields 

the equivalent formulation in Equation (4): 

 √ 

 (4) 

Computer Simulations 

The above derivations provide motivation to explore various proposed metrics that can be created from 

ball bar measurements and compared to the canonical test result for equivalency. To explore the 

implications of proposed methods such as Equations (3) and (4) a large number of different scenarios 

are computed. Each scenario is defined by a long range distribution N[μLR, LR], and a short range 

distribution N[μSize/2, SR] which models the short range errors are expected to have mean zero, and the 

size error is a source of bias denoted μSize/2 which is one half the size bias (the canonical artifacts are 

probed on each end and their sum yields the size bias). For a given scenario, the simulation involves an 

ISO 10360-5 test to evaluate the PS and PF values (using the default 25 point sampling strategy and a 

least squares fitting algorithm) and then the evaluation of 35 lengths each repeated three times. Each 

of the 35 lengths will have a different error drawn from the N[μLR, LR] distribution, and each probing 

point associated with the three repeated measurements has a different error drawn from the 

N[μSize/2, SR] distribution. A canonical measurement involves measuring the length with one probing 

point on each end of the length. The ball bar measurement involves taking many points (for 

convenience the 25 point ISO pattern is selected) on each ball. The long range error associated with the 

ball bar measurement is the same as that with the corresponding canonical length measurement12 but 

each probing point on the ball surface has a different error drawn from N[μSize/2, SR]. The canonical test 

result is computed and also the various proposed equivalent test results. This entire process is repeated 

1000 times for a given scenario in order to create a large sample to test results. 

To explore the different proposed methods of combining short and long range errors, a total of 81 

different scenarios were examined. In particular, three levels of each bias and standard deviation were 

examined so that scenarios would cover the cases for each of these parameters being less than, 

comparable, and greater than each other parameters; 34 =81 scenarios. In the actual simulation the 

levels of 0.001, 0.003, and 0.010 were selected for both the biases and standard deviations, and the 

nominal length of the artifacts was 1 meter. However, the particular numerical values of these levels is 

not critical, only their relative values are significant for testing the proposed methods. 

 

12 The same long range error is used because physically the ball bar is located in the same position and orientation 

within the CMM as the canonical artifact. 

6

6
Nine different computations of test results based on ball bar measurements are considered and 

compared to the canonical case; the metrics are described below. 

Metric 1: √ 

 This is the same as Equation (3).

Metric 2: √ 

 

 This is Metric 1 with the MPE values in place of the 

test result values for PS and PF. The MPE values are defined as the mean value plus two 

standard deviations as evaluated from the 1000 cycles. 

Metric 3: √ 

 This metric accounts for the size error by adding the PS value to each 

of the 105 center-to-center lengths and then determining the largest error regardless of sign, 

then this is combined in quadrature with the PF value. 

Metric 4: √ 

 This is Equation (4) which involves a ball bar with spheres calibrated for 

diameter 

Metric 5: √ 

 

 This is Metric 4 with the MPE value in place of the particular 

cycle PF value. 

Metric 6: √ 

 

 This is Metric 3 with the MPE value in place of the particular 

cycle PF value. 

Metric 7: | | this metric arithmetically combines the center-to-center statistic with 

the absolute value of the PS test result and the PF test result. 

Metric 8: this is Metric 7 with the MPE values in place of the PS and 

PF test results. 

Metric 9: Max[ | | This metric selects the larger case 

(regardless of sign) of adding or subtracting the PF value to the and PS values. 

Simulation Results 

The numerical results for the nine metrics and 81 scenarios are included in tables at the end of this 

paper. Since the central issue is the equivalency of a proposed metric to that of the canonical case, 

examining the mean of the difference between each proposed metric and the canonical result, scaled by 

the canonical, is useful; in the tables at the end of this paper this is denoted Mean[(Metric_X – Bi )/Bi], 

where Metric_X is the test result for the X

th metric, and Bi is the test result for the canonical case. This 

quantity presents the difference between the proposed test result of metric X and the canonical test 

result as a fraction of the canonical test value. Note that this difference in the two metrics is computed 

for each cycle of the 1000 cycles and then the mean of this quantity is computed for each scenario. This 

7

7
is done for all 81 scenarios and presented as a scatter chart in Figure 2 for all 9 different metrics. From 

Figure 2 it is clear that Metrics 1, 3, and 4 have, on average, test results that are within 10 % of the 

corresponding canonical value. For comparison, if the quantity (Bi_1-Bi_2)/Bi_2 is examined, where 

Bi_1 and Bi_2 are just repeats of the canonical test, the standard deviation of this quantity is between 

0.03 and 0.2 depending on the particular scenario; hence Metrics 1, 3, and 4 can be considered 

“equivalent” in the sense that their expected differences from the canonical case are no greater than 

the standard deviation of two canonical results similarly differenced and scaled. 

Metrics 5 and 6 use the MPE(PF) value and not surprisingly the metrics overestimate relative to the 

canonical value by as much as 40 %. Metric 2 use both MPE(PS) and MPE(PF) and overestimates by as 

much as 80 %. Metrics 7, 8, 9 are arithmetic sums of test results, and these metrics have been discussed 

in Standards Committees as possible useful test results; all of these metrics include scenarios that 

overestimate by as much as 40 %. 

Figure 2: The mean difference of each of the nine computed metrics relative to the canonical result, as a 

fraction of the canonical result (the ratio is unitless). 

A measure of the dispersion of the various metrics is shown in Figure 3, which displays the standard 

deviation of the 1000 test results per scenario divided by the corresponding canonical measurement 

standard deviation. Not surprisingly, those metrics that include MPEs, which are fixed quantities (for 

each scenario) show less variation. Metrics 3 and 4 show less variation than Metric 1, perhaps because 

the size error is included in the length measurement before the order statistic is computed. 

-0.2000

0.0000

0.2000

0.4000

0.6000

0.8000

1.0000

1.2000

0 1 2 3 4 5 6 7 8 9 10

Metric Number

Mean[ Metric1-Bi/Bi]

Mean[ Metric2-Bi/Bi]

Mean[ Metric3-Bi/Bi]

Mean[ Metric4-Bi/Bi]

Mean[ Metric5-Bi/Bi]

Mean[ Metric6-Bi/Bi]

Mean[ Metric7-Bi/Bi]

Mean[ Metric8-Bi/Bi]

Mean[ Metric9-Bi/Bi]

8

8
Figure 3: The ratio of the standard deviation of each of the nine computed metrics to that of the 

canonical case (the ratio is unitless). 

Summary 

Of the nine metrics examined in an effort to produce a test result based on ball bar measurements but 

equivalent to a (bi-directional) canonical test result (which is the 105th order statistic of 105 length 

errors), only Metrics 3 and 4 appear reasonable for the case of Gaussianly distributed errors. If the 

probing errors are known to be non-Gaussian then this particular error distribution must be investigated 

before claims of equivalency can be asserted. 

0.0000

0.2000

0.4000

0.6000

0.8000

1.0000

1.2000

1.4000

1.6000

1.8000

2.0000

0 1 2 3 4 5 6 7 8 9 10

Metric Number

SD[Metric1]/SDBi

SD[Metric2]/SDBi

SD[Metric3]/SDBi

SD[Metric4]/SDBi

SD[Metric5]/SDBi

SD[Metric6]/SDBi

SD[Metric8]/SDBi

SD[Metric9]/SDBi

SD[Metric7]/SDBi

9

9
Annex A: Discussion of order statistics 

The test results as specified in CMM standards often employ order statistics, e.g., the largest observed 

error of 105 measurements regardless of sign. Some error sources may be fixed during all 105 

measurements, such as the error associated with the effective probe size, so it is important to note that 

the addition of this fixed error to each individual length measurement results in a different value than 

adding this fixed error onto the order statistic found from the length measurements without the fixed 

error included. 

The simplest way to see this is to consider a uniform distribution from -1 to +1. Partition the distribution 

into 10 bins. The probability of drawing a value from one of the extreme bins (near ±1) is 2 out of 10. 

Now draw a sample of size N elements and take their absolute values, with N just large enough that the 

Nth order statistic had the expectation in an extreme bin, e.g., 0.91. Consider adding a fixed constant, 

e.g., 0.5, onto this result which yields 1.41. Alternatively, add the 0.5 to all N values, this is equivalent to 

shifting the uniform distribution to between -0.5 and +1.5, however now the probability of drawing a 

value in the extreme bin, i.e., 1.4 to 1.5, is now just 1 out of 10. For the case (above) where sample size 

of N was selected just large enough to yield an expected value in the extreme bin, the shifted 

distribution – with half the probability of drawing extreme values -- will cause the expectation value of 

the order statistic to yield a lower value. Letting the bin sizes become arbitrarily small, it is clear that the 

expectation value of the order statistic for the 0.5 to 1.5 distribution will be less than the -1 to 1 

distribution regardless of the size of N. 

Another way to think of this is effect is that the absolute value requirement “folds” the negative portion 

of the distribution back into the positive side creating a new distribution. For the -1 to +1 case this 

becomes a uniform distribution from 0 to +1, but for the -0.5 to +1.5 case it, the distribution becomes 

stepped, with the probability density being twice as large for the region 0 to 0.5 as in the region 0.5 to 

1.5; not surprisingly changing the distribution changes the expectation value of the order statistics. 

References 

 

1 ISO 10360-2:2009(E) Geometrical product specifications (GPS) — Acceptance and reverification tests for 

coordinate measuring machines (CMM) — Part 2: CMMs used for measuring linear dimensions 

2 ASME B89.4.10360.2-2008 Acceptance Test and Reverification Test for Coordinate Measuring Machines (CMMs) 

— Part 2: CMMs Used for Measuring Linear Dimensions, 2008; www.asme.org 

3 ISO 10360-5: 2010 (E) Geometrical product specifications (GPS) — Acceptance and reverification tests for 

coordinate measuring machines (CMM) — Part 5: CMMs using single and multiple stylus contacting probing 

systems 

4 ISO 2nd DIS 10360-8: Geometrical Product Specifications (GPS) — Acceptance and reverification tests for 

coordinate measuring machines (CMM) — Part 8: CMMs with optical distance sensors (dated 2012-03-13). 

10 10
Scenario number 1 2 3 4 5 6 7 8 9 10 11

longRangeErrorDist N[0.,0.001] N[0.,0.001] N[0.,0.001] N[0.,0.003] N[0.,0.003] N[0.,0.003] N[0.,0.010] N[0.,0.010] N[0.,0.010] N[0.,0.001] N[0.,0.001]

probeRndErrorDist N[0.,0.001] N[0.,0.003] N[0.,0.010] N[0.,0.001] N[0.,0.003] N[0.,0.010] N[0.,0.001] N[0.,0.003] N[0.,0.010] N[0.0015,0.001] N[0.0015,0.003]

Mean[Bi] 0.0048 0.0120 0.0391 0.0087 0.0143 0.0400 0.0250 0.0287 0.0477 0.0073 0.0140

stdDevBi 0.0007 0.0018 0.0055 0.0013 0.0020 0.0058 0.0043 0.0046 0.0069 0.0007 0.0018

Mean[Metric1] 0.0047 0.0121 0.0395 0.0084 0.0141 0.0399 0.0244 0.0276 0.0474 0.0077 0.0151

SD[Metric1] 0.0009 0.0027 0.0095 0.0014 0.0027 0.0089 0.0044 0.0045 0.0095 0.0009 0.0026

Mean[Metric1-Bi] 0.0000 0.0001 0.0004 -0.0003 -0.0001 0.0000 -0.0006 -0.0011 -0.0003 0.0004 0.0011

SD[Metric1-Bi] 0.0011 0.0032 0.0111 0.0012 0.0033 0.0111 0.0013 0.0034 0.0113 0.0011 0.0031

Mean[ Metric1-Bi/Bi] 0.0141 0.0269 0.0309 -0.0249 0.0087 0.0217 -0.0239 -0.0314 0.0120 0.0642 0.0969

SD[ Metric1-Bi/Bi] 0.2371 0.2674 0.2885 0.1347 0.2370 0.2761 0.0521 0.1187 0.2410 0.1585 0.2320

SD[Metric1]/SDBi 1.3201 1.4592 1.7367 1.0129 1.3114 1.5317 1.0184 0.9853 1.3871 1.1874 1.4493

SD[Metric1-Bi]/SDBi 1.6120 1.7369 2.0217 0.8622 1.6206 1.9062 0.2907 0.7450 1.6468 1.5294 1.7603

Mean[Metric2] 0.0072 0.0199 0.0657 0.0105 0.0213 0.0657 0.0260 0.0336 0.0721 0.0101 0.0227

SD[Metric2] 0.0003 0.0002 0.0006 0.0011 0.0008 0.0008 0.0043 0.0038 0.0025 0.0002 0.0002

Mean[Metric2-Bi] 0.0024 0.0078 0.0266 0.0018 0.0070 0.0257 0.0010 0.0048 0.0244 0.0028 0.0086

SD[Metric2-Bi] 0.0007 0.0018 0.0054 0.0009 0.0021 0.0059 0.0010 0.0028 0.0067 0.0008 0.0018

Mean[ Metric2-Bi/Bi] 0.5374 0.6852 0.7118 0.2203 0.5172 0.6773 0.0439 0.1814 0.5411 0.3926 0.6423

SD[ Metric2-Bi/Bi] 0.2128 0.2461 0.2311 0.1289 0.2131 0.2344 0.0454 0.1159 0.2107 0.1378 0.2039

SD[Metric2]/SDBi 0.3656 0.1292 0.1043 0.8043 0.3687 0.1313 0.9823 0.8356 0.3687 0.3248 0.1376

SD[Metric2-Bi]/SDBi 0.9987 1.0063 0.9920 0.6819 1.0218 1.0102 0.2409 0.6036 0.9727 1.0137 1.0135

Mean[Metric3] 0.0049 0.0127 0.0411 0.0086 0.0148 0.0418 0.0245 0.0281 0.0494 0.0068 0.0136

SD[Metric3] 0.0006 0.0020 0.0066 0.0013 0.0019 0.0066 0.0043 0.0043 0.0068 0.0008 0.0019

Mean[Metric3-Bi] 0.0002 0.0006 0.0020 -0.0001 0.0005 0.0019 -0.0005 -0.0006 0.0018 -0.0005 -0.0005

SD[Metric3-Bi] 0.0009 0.0027 0.0084 0.0011 0.0028 0.0091 0.0012 0.0032 0.0090 0.0010 0.0026

Mean[ Metric3-Bi/Bi] 0.0580 0.0730 0.0704 -0.0054 0.0556 0.0690 -0.0199 -0.0130 0.0558 -0.0669 -0.0177

SD[ Metric3-Bi/Bi] 0.1963 0.2277 0.2216 0.1247 0.2040 0.2322 0.0479 0.1134 0.1993 0.1325 0.1860

SD[Metric3]/SDBi 0.9296 1.0820 1.2094 0.9372 0.9489 1.1348 0.9922 0.9322 0.9906 1.0449 1.0977

SD[Metric3-Bi]/SDBi 1.3234 1.4574 1.5313 0.8076 1.3789 1.5682 0.2712 0.7058 1.3175 1.3576 1.4766

Mean[Metric4] 0.0049 0.0127 0.0414 0.0087 0.0147 0.0420 0.0246 0.0284 0.0491 0.0070 0.0141

SD[Metric4] 0.0006 0.0019 0.0063 0.0012 0.0018 0.0061 0.0043 0.0042 0.0063 0.0006 0.0017

Mean[Metric4-Bi] 0.0002 0.0007 0.0023 -0.0001 0.0004 0.0020 -0.0004 -0.0004 0.0015 -0.0003 0.0001

SD[Metric4-Bi] 0.0009 0.0026 0.0082 0.0010 0.0027 0.0088 0.0011 0.0031 0.0087 0.0009 0.0024

Mean[ Metric4-Bi/Bi] 0.0517 0.0784 0.0780 0.0025 0.0498 0.0735 -0.0159 -0.0050 0.0493 -0.0365 0.0223

SD[ Metric4-Bi/Bi] 0.1901 0.2219 0.2184 0.1166 0.1909 0.2242 0.0448 0.1074 0.1909 0.1134 0.1751

SD[Metric4]/SDBi 0.8845 1.0215 1.1592 0.9053 0.8675 1.0551 0.9923 0.9084 0.9206 0.7738 0.9681

SD[Metric4-Bi]/SDBi 1.2846 1.4118 1.5013 0.7446 1.2964 1.5070 0.2502 0.6657 1.2756 1.1656 1.3732

Mean[Metric5] 0.0060 0.0164 0.0540 0.0093 0.0177 0.0543 0.0248 0.0302 0.0601 0.0078 0.0174

SD[Metric5] 0.0003 0.0004 0.0010 0.0011 0.0009 0.0011 0.0043 0.0039 0.0029 0.0004 0.0005

Mean[Metric5-Bi] 0.0012 0.0044 0.0149 0.0006 0.0034 0.0143 -0.0002 0.0015 0.0124 0.0004 0.0034

SD[Metric5-Bi] 0.0007 0.0019 0.0055 0.0009 0.0021 0.0059 0.0011 0.0029 0.0068 0.0008 0.0018

Mean[ Metric5-Bi/Bi] 0.2762 0.3951 0.4078 0.0827 0.2629 0.3862 -0.0060 0.0617 0.2839 0.0679 0.2594

SD[ Metric5-Bi/Bi] 0.1794 0.2055 0.1914 0.1157 0.1786 0.1945 0.0445 0.1083 0.1776 0.1082 0.1598

SD[Metric5]/SDBi 0.4191 0.2047 0.1881 0.8183 0.4160 0.1959 0.9829 0.8391 0.4262 0.5608 0.2926

SD[Metric5-Bi]/SDBi 1.0138 1.0167 1.0020 0.6950 1.0272 1.0112 0.2483 0.6386 0.9959 1.0371 1.0400

Mean[Metric6] 0.0064 0.0174 0.0569 0.0097 0.0191 0.0574 0.0248 0.0310 0.0647 0.0086 0.0189

SD[Metric6] 0.0003 0.0004 0.0010 0.0012 0.0010 0.0012 0.0043 0.0041 0.0033 0.0004 0.0005

Mean[Metric6-Bi] 0.0017 0.0053 0.0178 0.0010 0.0048 0.0174 -0.0002 0.0023 0.0170 0.0012 0.0048

SD[Metric6-Bi] 0.0007 0.0019 0.0055 0.0012 0.0022 0.0059 0.0016 0.0037 0.0070 0.0008 0.0018

Mean[ Metric6-Bi/Bi] 0.3743 0.4729 0.4826 0.1264 0.3594 0.4641 -0.0040 0.0924 0.3830 0.1806 0.3670

SD[ Metric6-Bi/Bi] 0.1946 0.2178 0.2004 0.1460 0.1950 0.2061 0.0639 0.1347 0.1930 0.1165 0.1731

SD[Metric6]/SDBi 0.4836 0.2227 0.1892 0.8750 0.4978 0.2111 0.9881 0.8924 0.4775 0.5537 0.2751

SD[Metric6-Bi]/SDBi 1.0420 1.0282 1.0012 0.8735 1.0577 1.0221 0.3589 0.7959 1.0186 1.0232 1.0395

Mean[Metric7] 0.0071 0.0175 0.0559 0.0118 0.0214 0.0576 0.0283 0.0379 0.0714 0.0096 0.0191

SD[Metric7] 0.0009 0.0026 0.0083 0.0015 0.0027 0.0085 0.0044 0.0050 0.0095 0.0010 0.0027

Mean[Metric7-Bi] 0.0024 0.0054 0.0167 0.0031 0.0071 0.0176 0.0033 0.0092 0.0237 0.0023 0.0051

SD[Metric7-Bi] 0.0011 0.0031 0.0096 0.0013 0.0034 0.0106 0.0013 0.0036 0.0109 0.0013 0.0032

Mean[ Metric7-Bi/Bi] 0.5299 0.4835 0.4529 0.3681 0.5278 0.4713 0.1381 0.3331 0.5232 0.3224 0.3841

SD[ Metric7-Bi/Bi] 0.2813 0.3036 0.2837 0.1731 0.2877 0.3059 0.0628 0.1530 0.2810 0.1892 0.2620

SD[Metric7]/SDBi 1.3063 1.3988 1.5228 1.1204 1.3163 1.4660 1.0178 1.0929 1.3862 1.3964 1.5269

SD[Metric7-Bi]/SDBi 1.5985 1.7014 1.7568 0.9315 1.6447 1.8179 0.3071 0.7907 1.5921 1.6814 1.8272

Mean[Metric8] 0.0093 0.0240 0.0779 0.0140 0.0276 0.0792 0.0305 0.0445 0.0935 0.0122 0.0268

SD[Metric8] 0.0005 0.0007 0.0020 0.0013 0.0014 0.0024 0.0044 0.0045 0.0048 0.0005 0.0007

Mean[Metric8-Bi] 0.0045 0.0120 0.0388 0.0053 0.0134 0.0393 0.0055 0.0158 0.0459 0.0049 0.0128

SD[Metric8-Bi] 0.0008 0.0020 0.0056 0.0010 0.0023 0.0063 0.0011 0.0029 0.0073 0.0008 0.0019

Mean[ Metric8-Bi/Bi] 0.9930 1.0390 1.0285 0.6304 0.9724 1.0223 0.2277 0.5681 0.9979 0.6860 0.9450

SD[ Metric8-Bi/Bi] 0.2795 0.3021 0.2740 0.1747 0.2823 0.2880 0.0616 0.1584 0.2745 0.1708 0.2474

SD[Metric8]/SDBi 0.6974 0.3943 0.3684 0.9592 0.6946 0.4110 1.0027 0.9706 0.6988 0.6154 0.4155

SD[Metric8-Bi]/SDBi 1.1064 1.0693 1.0240 0.7161 1.1428 1.0842 0.2430 0.6251 1.0607 1.1086 1.0936

Mean[Metric9] 0.0069 0.0171 0.0548 0.0114 0.0207 0.0564 0.0278 0.0368 0.0692 0.0093 0.0187

SD[Metric9] 0.0009 0.0025 0.0083 0.0015 0.0027 0.0084 0.0044 0.0050 0.0094 0.0011 0.0027

Mean[Metric9-Bi] 0.0022 0.0050 0.0157 0.0027 0.0064 0.0164 0.0028 0.0081 0.0216 0.0020 0.0047

SD[Metric9-Bi] 0.0011 0.0031 0.0096 0.0013 0.0034 0.0105 0.0013 0.0038 0.0108 0.0012 0.0032

Mean[ Metric9-Bi/Bi] 0.4818 0.4493 0.4255 0.3228 0.4794 0.4417 0.1184 0.2942 0.4783 0.2820 0.3551

SD[ Metric9-Bi/Bi] 0.2724 0.2975 0.2821 0.1734 0.2834 0.3023 0.0613 0.1568 0.2757 0.1823 0.2574

SD[Metric9]/SDBi 1.2868 1.3765 1.5129 1.1229 1.3188 1.4454 1.0161 1.0842 1.3648 1.4140 1.5102

SD[Metric9-Bi]/SDBi 1.5757 1.6847 1.7592 0.9619 1.6494 1.8105 0.3104 0.8274 1.5824 1.6455 1.8080

formMean 0.0036 0.0110 0.0365 0.0037 0.0109 0.0364 0.0037 0.0110 0.0363 0.0036 0.0110

formStdDev 0.0007 0.0021 0.0070 0.0007 0.0019 0.0069 0.0007 0.0021 0.0070 0.0007 0.0020

Points per sphere 25 25 25 25 25 25 25 25 25 25 25

Scenario number 1 2 3 4 5 6 7 8 9 10 11

11 11
Scenario number

longRangeErrorDist 

probeRndErrorDist 

Mean[Bi] 

stdDevBi 

Mean[Metric1] 

SD[Metric1] 

Mean[Metric1-Bi] 

SD[Metric1-Bi] 

Mean[ Metric1-Bi/Bi]

SD[ Metric1-Bi/Bi] 

SD[Metric1]/SDBi 

SD[Metric1-Bi]/SDBi

Mean[Metric2] 

SD[Metric2] 

Mean[Metric2-Bi] 

SD[Metric2-Bi] 

Mean[ Metric2-Bi/Bi]

SD[ Metric2-Bi/Bi] 

SD[Metric2]/SDBi 

SD[Metric2-Bi]/SDBi

Mean[Metric3] 

SD[Metric3] 

Mean[Metric3-Bi] 

SD[Metric3-Bi] 

Mean[ Metric3-Bi/Bi]

SD[ Metric3-Bi/Bi] 

SD[Metric3]/SDBi 

SD[Metric3-Bi]/SDBi

Mean[Metric4] 

SD[Metric4] 

Mean[Metric4-Bi] 

SD[Metric4-Bi] 

Mean[ Metric4-Bi/Bi]

SD[ Metric4-Bi/Bi] 

SD[Metric4]/SDBi 

SD[Metric4-Bi]/SDBi

Mean[Metric5] 

SD[Metric5] 

Mean[Metric5-Bi] 

SD[Metric5-Bi] 

Mean[ Metric5-Bi/Bi]

SD[ Metric5-Bi/Bi] 

SD[Metric5]/SDBi 

SD[Metric5-Bi]/SDBi

Mean[Metric6] 

SD[Metric6] 

Mean[Metric6-Bi] 

SD[Metric6-Bi] 

Mean[ Metric6-Bi/Bi]

SD[ Metric6-Bi/Bi] 

SD[Metric6]/SDBi 

SD[Metric6-Bi]/SDBi

Mean[Metric7] 

SD[Metric7] 

Mean[Metric7-Bi] 

SD[Metric7-Bi] 

Mean[ Metric7-Bi/Bi]

SD[ Metric7-Bi/Bi] 

SD[Metric7]/SDBi 

SD[Metric7-Bi]/SDBi

Mean[Metric8] 

SD[Metric8] 

Mean[Metric8-Bi] 

SD[Metric8-Bi] 

Mean[ Metric8-Bi/Bi]

SD[ Metric8-Bi/Bi] 

SD[Metric8]/SDBi 

SD[Metric8-Bi]/SDBi

Mean[Metric9] 

SD[Metric9] 

Mean[Metric9-Bi] 

SD[Metric9-Bi] 

Mean[ Metric9-Bi/Bi]

SD[ Metric9-Bi/Bi] 

SD[Metric9]/SDBi 

SD[Metric9-Bi]/SDBi

formMean 

formStdDev 

Points per sphere

Scenario number

12 13 14 15 16 17 18 19 20 21

N[0.,0.001] N[0.,0.003] N[0.,0.003] N[0.,0.003] N[0.,0.010] N[0.,0.010] N[0.,0.010] N[0.,0.001] N[0.,0.001] N[0.,0.001]

N[0.0015,0.010] N[0.0015,0.001] N[0.0015,0.003] N[0.0015,0.010] N[0.0015,0.001] N[0.0015,0.003] N[0.0015,0.010] N[0.005,0.001] N[0.005,0.003] N[0.005,0.010]

0.0398 0.0109 0.0161 0.0407 0.0261 0.0297 0.0483 0.0144 0.0210 0.0456

0.0056 0.0015 0.0022 0.0059 0.0046 0.0048 0.0070 0.0008 0.0019 0.0060

0.0427 0.0115 0.0173 0.0431 0.0275 0.0308 0.0508 0.0147 0.0221 0.0492

0.0094 0.0014 0.0027 0.0090 0.0044 0.0047 0.0091 0.0009 0.0028 0.0094

0.0029 0.0006 0.0012 0.0025 0.0014 0.0011 0.0024 0.0004 0.0011 0.0036

0.0108 0.0016 0.0034 0.0108 0.0028 0.0040 0.0109 0.0011 0.0034 0.0108

0.0930 0.0678 0.0937 0.0822 0.0637 0.0467 0.0688 0.0290 0.0618 0.0952

0.2838 0.1640 0.2224 0.2734 0.1169 0.1417 0.2342 0.0787 0.1645 0.2450

1.6936 0.9398 1.2424 1.5442 0.9591 0.9716 1.3105 1.2260 1.4589 1.5655

1.9442 1.0742 1.5768 1.8444 0.6078 0.8312 1.5674 1.4879 1.7917 1.8071

0.0690 0.0135 0.0244 0.0692 0.0291 0.0364 0.0757 0.0172 0.0298 0.0754

0.0006 0.0011 0.0008 0.0008 0.0043 0.0039 0.0026 0.0003 0.0002 0.0006

0.0292 0.0026 0.0083 0.0285 0.0030 0.0067 0.0274 0.0029 0.0089 0.0298

0.0056 0.0014 0.0022 0.0059 0.0027 0.0034 0.0069 0.0007 0.0019 0.0060

0.7652 0.2531 0.5435 0.7345 0.1267 0.2427 0.5967 0.2027 0.4333 0.6814

0.2403 0.1608 0.2043 0.2388 0.1180 0.1433 0.2215 0.0609 0.1264 0.2143

0.1086 0.7312 0.3465 0.1343 0.9344 0.8139 0.3704 0.3482 0.1300 0.0967

1.0056 0.9135 1.0035 1.0008 0.5798 0.7022 0.9945 0.9903 1.0108 1.0051

0.0418 0.0105 0.0159 0.0424 0.0255 0.0290 0.0502 0.0132 0.0183 0.0437

0.0066 0.0015 0.0022 0.0064 0.0045 0.0047 0.0068 0.0009 0.0021 0.0069

0.0020 -0.0004 -0.0002 0.0017 -0.0006 -0.0007 0.0019 -0.0012 -0.0027 -0.0019

0.0086 0.0012 0.0029 0.0087 0.0013 0.0034 0.0090 0.0010 0.0029 0.0089

0.0703 -0.0345 0.0031 0.0632 -0.0216 -0.0171 0.0575 -0.0784 -0.1198 -0.0273

0.2240 0.1067 0.1794 0.2183 0.0507 0.1153 0.1927 0.0668 0.1294 0.1937

1.1817 0.9921 1.0019 1.0971 0.9827 0.9681 0.9737 1.1329 1.1223 1.1523

1.5375 0.7733 1.3201 1.4900 0.2823 0.7122 1.2913 1.3209 1.5140 1.4939

0.0425 0.0107 0.0163 0.0431 0.0256 0.0293 0.0502 0.0135 0.0193 0.0458

0.0062 0.0014 0.0018 0.0061 0.0045 0.0046 0.0064 0.0006 0.0014 0.0058

0.0026 -0.0003 0.0002 0.0024 -0.0005 -0.0005 0.0019 -0.0009 -0.0017 0.0002

0.0083 0.0010 0.0026 0.0084 0.0012 0.0030 0.0088 0.0008 0.0024 0.0083

0.0864 -0.0186 0.0269 0.0800 -0.0170 -0.0091 0.0577 -0.0598 -0.0743 0.0214

0.2197 0.0919 0.1615 0.2118 0.0458 0.1019 0.1904 0.0554 0.1070 0.1828

1.1218 0.9134 0.8306 1.0393 0.9787 0.9512 0.9191 0.7773 0.7569 0.9669

1.4924 0.6638 1.1733 1.4332 0.2562 0.6273 1.2728 1.1156 1.2503 1.3844

0.0550 0.0112 0.0191 0.0550 0.0258 0.0310 0.0610 0.0139 0.0217 0.0570

0.0011 0.0013 0.0010 0.0013 0.0044 0.0043 0.0030 0.0005 0.0007 0.0014

0.0151 0.0003 0.0031 0.0144 -0.0002 0.0013 0.0127 -0.0005 0.0007 0.0114

0.0057 0.0010 0.0022 0.0059 0.0012 0.0028 0.0071 0.0008 0.0020 0.0061

0.4063 0.0316 0.2098 0.3805 -0.0074 0.0538 0.2865 -0.0298 0.0433 0.2712

0.1948 0.0908 0.1596 0.1912 0.0458 0.1002 0.1824 0.0540 0.0969 0.1646

0.1999 0.8584 0.4735 0.2267 0.9686 0.8788 0.4360 0.7115 0.3887 0.2342

1.0285 0.6366 1.0033 1.0097 0.2551 0.5866 1.0231 1.0700 1.0569 1.0229

0.0586 0.0122 0.0212 0.0591 0.0267 0.0333 0.0670 0.0149 0.0239 0.0618

0.0011 0.0013 0.0011 0.0014 0.0045 0.0045 0.0035 0.0005 0.0006 0.0013

0.0188 0.0013 0.0051 0.0184 0.0006 0.0036 0.0186 0.0005 0.0029 0.0162

0.0057 0.0009 0.0022 0.0059 0.0014 0.0031 0.0071 0.0008 0.0020 0.0061

0.5007 0.1261 0.3391 0.4823 0.0253 0.1312 0.4115 0.0405 0.1463 0.3781

0.2065 0.0950 0.1725 0.2050 0.0553 0.1143 0.1981 0.0548 0.1044 0.1782

0.2031 0.8682 0.5183 0.2346 0.9925 0.9306 0.5094 0.6809 0.3395 0.2112

1.0220 0.6133 0.9880 1.0108 0.3020 0.6451 1.0245 1.0320 1.0454 1.0254

0.0569 0.0143 0.0231 0.0586 0.0309 0.0395 0.0726 0.0166 0.0259 0.0608

0.0084 0.0017 0.0031 0.0084 0.0045 0.0054 0.0094 0.0011 0.0030 0.0096

0.0171 0.0034 0.0070 0.0180 0.0048 0.0097 0.0242 0.0023 0.0050 0.0152

0.0100 0.0018 0.0037 0.0102 0.0029 0.0045 0.0109 0.0012 0.0036 0.0110

0.4560 0.3266 0.4595 0.4704 0.1963 0.3452 0.5282 0.1599 0.2466 0.3547

0.2930 0.2015 0.2671 0.2916 0.1323 0.1813 0.2736 0.0905 0.1828 0.2680

1.5021 1.0966 1.4195 1.4301 0.9903 1.1070 1.3558 1.4385 1.5647 1.6040

1.7900 1.1806 1.6824 1.7406 0.6315 0.9333 1.5716 1.6435 1.8826 1.8426

0.0812 0.0170 0.0308 0.0827 0.0336 0.0473 0.0972 0.0194 0.0340 0.0876

0.0021 0.0013 0.0014 0.0025 0.0044 0.0046 0.0049 0.0005 0.0007 0.0020

0.0414 0.0061 0.0148 0.0420 0.0075 0.0176 0.0489 0.0050 0.0130 0.0420

0.0059 0.0015 0.0024 0.0062 0.0027 0.0035 0.0076 0.0008 0.0020 0.0063

1.0777 0.5772 0.9510 1.0741 0.3048 0.6167 1.0491 0.3520 0.6324 0.9518

0.2869 0.2009 0.2618 0.2892 0.1375 0.1881 0.2863 0.0715 0.1484 0.2525

0.3823 0.8712 0.6580 0.4185 0.9545 0.9421 0.7022 0.6588 0.3922 0.3362

1.0680 0.9600 1.1023 1.0609 0.5842 0.7333 1.0998 1.0835 1.0811 1.0569

0.0559 0.0135 0.0223 0.0572 0.0289 0.0377 0.0703 0.0163 0.0255 0.0596

0.0084 0.0017 0.0030 0.0083 0.0046 0.0054 0.0093 0.0011 0.0030 0.0096

0.0160 0.0025 0.0062 0.0166 0.0028 0.0080 0.0220 0.0020 0.0045 0.0140

0.0100 0.0014 0.0035 0.0102 0.0015 0.0041 0.0107 0.0012 0.0035 0.0110

0.4291 0.2405 0.4059 0.4357 0.1115 0.2819 0.4803 0.1400 0.2254 0.3277

0.2917 0.1413 0.2502 0.2875 0.0641 0.1565 0.2658 0.0880 0.1806 0.2669

1.5052 1.1358 1.3940 1.4134 1.0112 1.1253 1.3414 1.4648 1.5657 1.6055

1.7982 0.9023 1.6064 1.7362 0.3210 0.8478 1.5453 1.6168 1.8717 1.8466

0.0369 0.0037 0.0110 0.0367 0.0037 0.0110 0.0369 0.0037 0.0110 0.0364

0.0070 0.0007 0.0020 0.0068 0.0007 0.0021 0.0069 0.0007 0.0020 0.0068

25 25 25 25 25 25 25 25 25 25

12 13 14 15 16 17 18 19 20 21

12 12
Scenario number

longRangeErrorDist 

probeRndErrorDist 

Mean[Bi] 

stdDevBi 

Mean[Metric1] 

SD[Metric1] 

Mean[Metric1-Bi] 

SD[Metric1-Bi] 

Mean[ Metric1-Bi/Bi]

SD[ Metric1-Bi/Bi] 

SD[Metric1]/SDBi 

SD[Metric1-Bi]/SDBi

Mean[Metric2] 

SD[Metric2] 

Mean[Metric2-Bi] 

SD[Metric2-Bi] 

Mean[ Metric2-Bi/Bi]

SD[ Metric2-Bi/Bi] 

SD[Metric2]/SDBi 

SD[Metric2-Bi]/SDBi

Mean[Metric3] 

SD[Metric3] 

Mean[Metric3-Bi] 

SD[Metric3-Bi] 

Mean[ Metric3-Bi/Bi]

SD[ Metric3-Bi/Bi] 

SD[Metric3]/SDBi 

SD[Metric3-Bi]/SDBi

Mean[Metric4] 

SD[Metric4] 

Mean[Metric4-Bi] 

SD[Metric4-Bi] 

Mean[ Metric4-Bi/Bi]

SD[ Metric4-Bi/Bi] 

SD[Metric4]/SDBi 

SD[Metric4-Bi]/SDBi

Mean[Metric5] 

SD[Metric5] 

Mean[Metric5-Bi] 

SD[Metric5-Bi] 

Mean[ Metric5-Bi/Bi]

SD[ Metric5-Bi/Bi] 

SD[Metric5]/SDBi 

SD[Metric5-Bi]/SDBi

Mean[Metric6] 

SD[Metric6] 

Mean[Metric6-Bi] 

SD[Metric6-Bi] 

Mean[ Metric6-Bi/Bi]

SD[ Metric6-Bi/Bi] 

SD[Metric6]/SDBi 

SD[Metric6-Bi]/SDBi

Mean[Metric7] 

SD[Metric7] 

Mean[Metric7-Bi] 

SD[Metric7-Bi] 

Mean[ Metric7-Bi/Bi]

SD[ Metric7-Bi/Bi] 

SD[Metric7]/SDBi 

SD[Metric7-Bi]/SDBi

Mean[Metric8] 

SD[Metric8] 

Mean[Metric8-Bi] 

SD[Metric8-Bi] 

Mean[ Metric8-Bi/Bi]

SD[ Metric8-Bi/Bi] 

SD[Metric8]/SDBi 

SD[Metric8-Bi]/SDBi

Mean[Metric9] 

SD[Metric9] 

Mean[Metric9-Bi] 

SD[Metric9-Bi] 

Mean[ Metric9-Bi/Bi]

SD[ Metric9-Bi/Bi] 

SD[Metric9]/SDBi 

SD[Metric9-Bi]/SDBi

formMean 

formStdDev 

Points per sphere

Scenario number

22 23 24 25 26 27 28 29 30 31

N[0.,0.003] N[0.,0.003] N[0.,0.003] N[0.,0.010] N[0.,0.010] N[0.,0.010] N[0.003,0.001] N[0.003,0.001] N[0.003,0.001] N[0.003,0.003]

N[0.005,0.001] N[0.005,0.003] N[0.005,0.010] N[0.005,0.001] N[0.005,0.003] N[0.005,0.010] N[0.,0.001] N[0.,0.003] N[0.,0.010] N[0.,0.001]

0.0180 0.0231 0.0462 0.0323 0.0357 0.0539 0.0073 0.0141 0.0401 0.0109

0.0016 0.0023 0.0062 0.0049 0.0051 0.0075 0.0007 0.0019 0.0058 0.0016

0.0185 0.0244 0.0498 0.0345 0.0375 0.0575 0.0068 0.0134 0.0398 0.0105

0.0014 0.0026 0.0090 0.0044 0.0046 0.0093 0.0009 0.0027 0.0091 0.0016

0.0005 0.0013 0.0036 0.0022 0.0018 0.0036 -0.0005 -0.0007 -0.0003 -0.0004

0.0015 0.0034 0.0108 0.0042 0.0050 0.0116 0.0011 0.0033 0.0106 0.0012

0.0333 0.0680 0.0953 0.0797 0.0635 0.0845 -0.0625 -0.0302 0.0102 -0.0312

0.0878 0.1511 0.2399 0.1534 0.1509 0.2220 0.1451 0.2358 0.2682 0.1085

0.8847 1.1132 1.4539 0.8967 0.9080 1.2399 1.1843 1.3947 1.5673 1.0119

0.9653 1.4744 1.7475 0.8610 0.9768 1.5436 1.4579 1.7525 1.8110 0.7612

0.0204 0.0315 0.0749 0.0360 0.0434 0.0821 0.0090 0.0209 0.0663 0.0124

0.0011 0.0007 0.0008 0.0043 0.0037 0.0025 0.0004 0.0004 0.0006 0.0013

0.0025 0.0084 0.0286 0.0037 0.0077 0.0282 0.0017 0.0068 0.0261 0.0015

0.0014 0.0023 0.0063 0.0041 0.0044 0.0077 0.0008 0.0019 0.0059 0.0010

0.1433 0.3770 0.6479 0.1274 0.2318 0.5503 0.2385 0.5085 0.6843 0.1445

0.0870 0.1343 0.2156 0.1561 0.1544 0.2089 0.1227 0.1995 0.2367 0.1001

0.7174 0.3121 0.1233 0.8799 0.7353 0.3291 0.5420 0.1924 0.1085 0.8471

0.8742 1.0120 1.0085 0.8483 0.8706 1.0167 1.0329 1.0205 1.0039 0.6099

0.0172 0.0214 0.0445 0.0317 0.0343 0.0529 0.0068 0.0136 0.0414 0.0105

0.0016 0.0023 0.0067 0.0048 0.0050 0.0076 0.0008 0.0020 0.0065 0.0016

-0.0007 -0.0017 -0.0018 -0.0006 -0.0014 -0.0011 -0.0005 -0.0005 0.0013 -0.0004

0.0012 0.0031 0.0091 0.0012 0.0036 0.0101 0.0010 0.0028 0.0086 0.0012

-0.0393 -0.0660 -0.0221 -0.0190 -0.0354 -0.0033 -0.0607 -0.0186 0.0526 -0.0305

0.0650 0.1272 0.1916 0.0385 0.0987 0.1859 0.1359 0.1992 0.2180 0.1058

1.0306 0.9928 1.0818 0.9834 0.9842 1.0159 1.0758 1.0573 1.1130 0.9937

0.7524 1.3236 1.4627 0.2534 0.6988 1.3486 1.3731 1.4921 1.4702 0.7445

0.0174 0.0220 0.0464 0.0319 0.0349 0.0543 0.0071 0.0142 0.0422 0.0107

0.0015 0.0018 0.0055 0.0048 0.0046 0.0063 0.0006 0.0017 0.0062 0.0014

-0.0005 -0.0011 0.0002 -0.0005 -0.0008 0.0004 -0.0002 0.0001 0.0020 -0.0002

0.0010 0.0027 0.0083 0.0011 0.0031 0.0093 0.0009 0.0026 0.0083 0.0010

-0.0275 -0.0401 0.0218 -0.0134 -0.0186 0.0241 -0.0258 0.0241 0.0709 -0.0148

0.0558 0.1109 0.1785 0.0350 0.0871 0.1726 0.1168 0.1830 0.2139 0.0946

0.9299 0.7665 0.8922 0.9783 0.9077 0.8330 0.8068 0.8755 1.0599 0.9050

0.6491 1.1542 1.3347 0.2323 0.6122 1.2363 1.1814 1.3483 1.4302 0.6653

0.0178 0.0242 0.0571 0.0321 0.0364 0.0643 0.0078 0.0174 0.0544 0.0112

0.0014 0.0013 0.0016 0.0047 0.0044 0.0034 0.0004 0.0005 0.0010 0.0013

-0.0002 0.0011 0.0109 -0.0003 0.0007 0.0104 0.0005 0.0033 0.0143 0.0003

0.0010 0.0024 0.0063 0.0011 0.0030 0.0076 0.0008 0.0020 0.0059 0.0010

-0.0094 0.0584 0.2573 -0.0074 0.0249 0.2138 0.0817 0.2574 0.3828 0.0349

0.0559 0.1071 0.1660 0.0349 0.0871 0.1619 0.1122 0.1680 0.1948 0.0946

0.9099 0.5746 0.2608 0.9719 0.8615 0.4472 0.5927 0.2729 0.1793 0.8544

0.6451 1.0469 1.0215 0.2309 0.5948 1.0042 1.0619 1.0295 1.0115 0.6396

0.0188 0.0267 0.0621 0.0331 0.0394 0.0711 0.0087 0.0190 0.0583 0.0123

0.0014 0.0013 0.0016 0.0047 0.0045 0.0036 0.0004 0.0005 0.0011 0.0014

0.0008 0.0036 0.0158 0.0008 0.0037 0.0172 0.0014 0.0049 0.0181 0.0013

0.0010 0.0024 0.0064 0.0011 0.0030 0.0076 0.0008 0.0020 0.0059 0.0010

0.0494 0.1648 0.3661 0.0260 0.1117 0.3420 0.1975 0.3719 0.4811 0.1311

0.0565 0.1141 0.1799 0.0347 0.0936 0.1771 0.1204 0.1834 0.2091 0.0987

0.9106 0.5403 0.2523 0.9749 0.8766 0.4745 0.5870 0.2584 0.1803 0.8679

0.6240 1.0237 1.0251 0.2202 0.5900 1.0037 1.0482 1.0358 1.0128 0.6130

0.0213 0.0301 0.0626 0.0379 0.0461 0.0767 0.0099 0.0202 0.0578 0.0140

0.0016 0.0031 0.0093 0.0045 0.0053 0.0106 0.0009 0.0024 0.0081 0.0017

0.0033 0.0070 0.0163 0.0055 0.0104 0.0228 0.0026 0.0061 0.0177 0.0031

0.0017 0.0038 0.0111 0.0042 0.0054 0.0126 0.0011 0.0031 0.0099 0.0013

0.1896 0.3157 0.3763 0.1862 0.3079 0.4481 0.3688 0.4599 0.4687 0.2939

0.1025 0.1813 0.2679 0.1646 0.1839 0.2696 0.1767 0.2625 0.2881 0.1356

1.0257 1.3183 1.5011 0.9169 1.0368 1.4024 1.2525 1.2574 1.3803 1.0764

1.0449 1.6211 1.7903 0.8699 1.0594 1.6722 1.5154 1.6375 1.6900 0.8114

0.0239 0.0379 0.0883 0.0405 0.0543 0.1035 0.0121 0.0266 0.0796 0.0162

0.0013 0.0014 0.0024 0.0044 0.0043 0.0047 0.0005 0.0008 0.0021 0.0015

0.0060 0.0148 0.0421 0.0082 0.0186 0.0496 0.0048 0.0125 0.0395 0.0053

0.0014 0.0026 0.0066 0.0042 0.0046 0.0084 0.0008 0.0021 0.0062 0.0010

0.3383 0.6585 0.9435 0.2697 0.5412 0.9550 0.6699 0.9235 1.0245 0.4973

0.1020 0.1658 0.2589 0.1716 0.1917 0.2673 0.1652 0.2588 0.2881 0.1345

0.8518 0.5983 0.3802 0.8986 0.8527 0.6288 0.7186 0.4170 0.3517 0.9482

0.9122 1.1016 1.0715 0.8545 0.9042 1.1161 1.1021 1.0882 1.0549 0.6277

0.0205 0.0292 0.0613 0.0351 0.0434 0.0741 0.0094 0.0187 0.0553 0.0135

0.0018 0.0031 0.0094 0.0049 0.0057 0.0106 0.0011 0.0028 0.0083 0.0018

0.0025 0.0061 0.0150 0.0028 0.0077 0.0202 0.0021 0.0046 0.0151 0.0026

0.0013 0.0037 0.0111 0.0014 0.0041 0.0124 0.0012 0.0035 0.0099 0.0014

0.1433 0.2766 0.3475 0.0897 0.2231 0.3971 0.2919 0.3517 0.4035 0.2468

0.0784 0.1746 0.2650 0.0486 0.1294 0.2606 0.1860 0.2765 0.2826 0.1406

1.1267 1.3383 1.5093 1.0050 1.1096 1.4151 1.4539 1.4781 1.4169 1.1335

0.8426 1.5904 1.7930 0.2919 0.8119 1.6486 1.6652 1.8255 1.7045 0.8779

0.0037 0.0110 0.0361 0.0037 0.0110 0.0368 0.0037 0.0110 0.0367 0.0037

0.0007 0.0020 0.0066 0.0007 0.0021 0.0069 0.0007 0.0020 0.0068 0.0007

25 25 25 25 25 25 25 25 25 25

22 23 24 25 26 27 28 29 30 31

13 13
Scenario number

longRangeErrorDist 

probeRndErrorDist 

Mean[Bi] 

stdDevBi 

Mean[Metric1] 

SD[Metric1] 

Mean[Metric1-Bi] 

SD[Metric1-Bi] 

Mean[ Metric1-Bi/Bi]

SD[ Metric1-Bi/Bi] 

SD[Metric1]/SDBi 

SD[Metric1-Bi]/SDBi

Mean[Metric2] 

SD[Metric2] 

Mean[Metric2-Bi] 

SD[Metric2-Bi] 

Mean[ Metric2-Bi/Bi]

SD[ Metric2-Bi/Bi] 

SD[Metric2]/SDBi 

SD[Metric2-Bi]/SDBi

Mean[Metric3] 

SD[Metric3] 

Mean[Metric3-Bi] 

SD[Metric3-Bi] 

Mean[ Metric3-Bi/Bi]

SD[ Metric3-Bi/Bi] 

SD[Metric3]/SDBi 

SD[Metric3-Bi]/SDBi

Mean[Metric4] 

SD[Metric4] 

Mean[Metric4-Bi] 

SD[Metric4-Bi] 

Mean[ Metric4-Bi/Bi]

SD[ Metric4-Bi/Bi] 

SD[Metric4]/SDBi 

SD[Metric4-Bi]/SDBi

Mean[Metric5] 

SD[Metric5] 

Mean[Metric5-Bi] 

SD[Metric5-Bi] 

Mean[ Metric5-Bi/Bi]

SD[ Metric5-Bi/Bi] 

SD[Metric5]/SDBi 

SD[Metric5-Bi]/SDBi

Mean[Metric6] 

SD[Metric6] 

Mean[Metric6-Bi] 

SD[Metric6-Bi] 

Mean[ Metric6-Bi/Bi]

SD[ Metric6-Bi/Bi] 

SD[Metric6]/SDBi 

SD[Metric6-Bi]/SDBi

Mean[Metric7] 

SD[Metric7] 

Mean[Metric7-Bi] 

SD[Metric7-Bi] 

Mean[ Metric7-Bi/Bi]

SD[ Metric7-Bi/Bi] 

SD[Metric7]/SDBi 

SD[Metric7-Bi]/SDBi

Mean[Metric8] 

SD[Metric8] 

Mean[Metric8-Bi] 

SD[Metric8-Bi] 

Mean[ Metric8-Bi/Bi]

SD[ Metric8-Bi/Bi] 

SD[Metric8]/SDBi 

SD[Metric8-Bi]/SDBi

Mean[Metric9] 

SD[Metric9] 

Mean[Metric9-Bi] 

SD[Metric9-Bi] 

Mean[ Metric9-Bi/Bi]

SD[ Metric9-Bi/Bi] 

SD[Metric9]/SDBi 

SD[Metric9-Bi]/SDBi

formMean 

formStdDev 

Points per sphere

Scenario number

32 33 34 35 36 37 38 39 40 41

N[0.003,0.003] N[0.003,0.003] N[0.003,0.010] N[0.003,0.010] N[0.003,0.010] N[0.003,0.001] N[0.003,0.001] N[0.003,0.001] N[0.003,0.003] N[0.003,0.003]

N[0.,0.003] N[0.,0.010] N[0.,0.001] N[0.,0.003] N[0.,0.010] N[0.0015,0.001] N[0.0015,0.003] N[0.0015,0.010] N[0.0015,0.001] N[0.0015,0.003]

0.0161 0.0412 0.0261 0.0295 0.0486 0.0104 0.0170 0.0422 0.0139 0.0190

0.0023 0.0061 0.0044 0.0051 0.0073 0.0008 0.0019 0.0058 0.0016 0.0023

0.0158 0.0409 0.0256 0.0286 0.0485 0.0098 0.0164 0.0429 0.0135 0.0186

0.0026 0.0088 0.0045 0.0050 0.0092 0.0009 0.0027 0.0090 0.0016 0.0027

-0.0004 -0.0003 -0.0006 -0.0009 -0.0001 -0.0005 -0.0006 0.0007 -0.0004 -0.0004

0.0033 0.0104 0.0012 0.0036 0.0113 0.0011 0.0032 0.0108 0.0012 0.0033

-0.0060 0.0122 -0.0216 -0.0241 0.0168 -0.0470 -0.0245 0.0368 -0.0266 -0.0105

0.2041 0.2553 0.0480 0.1252 0.2332 0.1037 0.1857 0.2625 0.0829 0.1743

1.1632 1.4373 1.0038 0.9761 1.2701 1.1109 1.4284 1.5314 0.9938 1.1943

1.4645 1.7048 0.2734 0.7138 1.5529 1.3769 1.7077 1.8431 0.7420 1.4542

0.0226 0.0662 0.0272 0.0346 0.0730 0.0120 0.0238 0.0687 0.0153 0.0257

0.0009 0.0009 0.0044 0.0041 0.0026 0.0004 0.0004 0.0006 0.0013 0.0009

0.0065 0.0250 0.0010 0.0051 0.0245 0.0016 0.0068 0.0265 0.0014 0.0067

0.0022 0.0062 0.0010 0.0029 0.0071 0.0008 0.0019 0.0059 0.0009 0.0022

0.4272 0.6423 0.0418 0.1867 0.5334 0.1603 0.4130 0.6592 0.1082 0.3686

0.1848 0.2346 0.0418 0.1196 0.2120 0.0853 0.1520 0.2283 0.0748 0.1527

0.4154 0.1448 0.9876 0.8045 0.3609 0.5060 0.1941 0.1072 0.8549 0.4148

0.9701 1.0081 0.2281 0.5732 0.9721 0.9840 1.0102 1.0078 0.6042 0.9693

0.0159 0.0422 0.0256 0.0288 0.0502 0.0095 0.0154 0.0421 0.0133 0.0179

0.0022 0.0062 0.0044 0.0046 0.0068 0.0008 0.0021 0.0066 0.0016 0.0024

-0.0002 0.0011 -0.0005 -0.0008 0.0016 -0.0009 -0.0016 -0.0001 -0.0006 -0.0011

0.0030 0.0085 0.0012 0.0034 0.0093 0.0011 0.0027 0.0088 0.0011 0.0030

0.0025 0.0466 -0.0199 -0.0172 0.0527 -0.0806 -0.0866 0.0162 -0.0385 -0.0473

0.1838 0.2109 0.0478 0.1171 0.1938 0.0968 0.1547 0.2139 0.0811 0.1555

0.9664 1.0078 0.9962 0.9139 0.9349 1.0389 1.1266 1.1332 1.0058 1.0389

1.3236 1.3939 0.2740 0.6764 1.2841 1.3092 1.4695 1.5102 0.7294 1.3261

0.0162 0.0427 0.0257 0.0290 0.0504 0.0097 0.0162 0.0435 0.0135 0.0186

0.0018 0.0059 0.0044 0.0045 0.0064 0.0006 0.0016 0.0061 0.0015 0.0019

0.0001 0.0016 -0.0004 -0.0005 0.0018 -0.0007 -0.0009 0.0013 -0.0004 -0.0005

0.0027 0.0083 0.0011 0.0032 0.0090 0.0009 0.0023 0.0084 0.0010 0.0027

0.0247 0.0593 -0.0146 -0.0089 0.0566 -0.0584 -0.0409 0.0502 -0.0235 -0.0125

0.1714 0.2068 0.0413 0.1094 0.1868 0.0801 0.1333 0.2072 0.0724 0.1415

0.8192 0.9656 0.9961 0.8892 0.8859 0.7304 0.8391 1.0422 0.9429 0.8198

1.2159 1.3613 0.2375 0.6342 1.2355 1.0910 1.2582 1.4373 0.6555 1.2025

0.0193 0.0544 0.0260 0.0310 0.0613 0.0103 0.0191 0.0554 0.0139 0.0212

0.0010 0.0013 0.0044 0.0041 0.0030 0.0005 0.0006 0.0012 0.0014 0.0012

0.0031 0.0132 -0.0002 0.0014 0.0127 -0.0001 0.0020 0.0132 0.0000 0.0022

0.0022 0.0062 0.0010 0.0031 0.0073 0.0008 0.0019 0.0059 0.0010 0.0023

0.2144 0.3485 -0.0057 0.0600 0.2870 -0.0016 0.1320 0.3382 0.0073 0.1275

0.1617 0.1930 0.0411 0.1101 0.1827 0.0778 0.1251 0.1857 0.0719 0.1298

0.4592 0.2203 0.9875 0.8139 0.4202 0.6093 0.3467 0.2132 0.9076 0.5314

0.9967 1.0170 0.2359 0.6049 1.0050 1.0255 1.0432 1.0176 0.6375 1.0082

0.0213 0.0586 0.0268 0.0335 0.0669 0.0112 0.0209 0.0595 0.0150 0.0235

0.0011 0.0014 0.0045 0.0044 0.0034 0.0005 0.0005 0.0011 0.0014 0.0012

0.0051 0.0174 0.0006 0.0040 0.0183 0.0009 0.0039 0.0173 0.0011 0.0045

0.0022 0.0062 0.0013 0.0032 0.0072 0.0008 0.0019 0.0060 0.0010 0.0022

0.3402 0.4536 0.0252 0.1474 0.4044 0.0896 0.2406 0.4362 0.0815 0.2518

0.1745 0.2093 0.0526 0.1240 0.1967 0.0823 0.1353 0.1994 0.0729 0.1413

0.4904 0.2253 1.0128 0.8686 0.4732 0.6010 0.2949 0.1892 0.9058 0.5310

0.9831 1.0211 0.2998 0.6391 0.9972 1.0093 1.0301 1.0212 0.6095 0.9906

0.0235 0.0593 0.0295 0.0388 0.0731 0.0124 0.0217 0.0581 0.0164 0.0251

0.0028 0.0079 0.0045 0.0054 0.0093 0.0011 0.0029 0.0084 0.0018 0.0031

0.0073 0.0182 0.0033 0.0093 0.0245 0.0020 0.0046 0.0159 0.0025 0.0060

0.0034 0.0099 0.0013 0.0039 0.0109 0.0013 0.0033 0.0102 0.0013 0.0036

0.4803 0.4712 0.1320 0.3290 0.5318 0.2009 0.2865 0.4023 0.1881 0.3338

0.2534 0.2846 0.0569 0.1605 0.2704 0.1300 0.2131 0.2818 0.1040 0.2129

1.2387 1.2934 1.0205 1.0610 1.2865 1.3762 1.5345 1.4406 1.1169 1.3693

1.5073 1.6148 0.2870 0.7659 1.5036 1.5777 1.7871 1.7516 0.8508 1.5839

0.0300 0.0808 0.0317 0.0458 0.0951 0.0151 0.0295 0.0821 0.0191 0.0331

0.0016 0.0025 0.0045 0.0047 0.0049 0.0005 0.0008 0.0020 0.0015 0.0016

0.0139 0.0396 0.0055 0.0162 0.0465 0.0047 0.0125 0.0399 0.0052 0.0141

0.0024 0.0066 0.0010 0.0030 0.0076 0.0008 0.0020 0.0062 0.0010 0.0024

0.8929 1.0039 0.2175 0.5727 0.9953 0.4632 0.7537 0.9821 0.3827 0.7613

0.2463 0.2910 0.0574 0.1645 0.2773 0.1080 0.1914 0.2773 0.0946 0.1976

0.6893 0.4089 1.0064 0.9283 0.6737 0.6713 0.4190 0.3474 0.9560 0.6842

1.0434 1.0736 0.2300 0.5843 1.0517 1.0334 1.0673 1.0650 0.6213 1.0387

0.0223 0.0571 0.0290 0.0375 0.0703 0.0124 0.0216 0.0567 0.0164 0.0249

0.0030 0.0080 0.0045 0.0055 0.0094 0.0011 0.0030 0.0087 0.0018 0.0032

0.0061 0.0159 0.0028 0.0080 0.0218 0.0020 0.0045 0.0145 0.0025 0.0059

0.0036 0.0099 0.0014 0.0041 0.0111 0.0013 0.0034 0.0105 0.0013 0.0037

0.4041 0.4155 0.1119 0.2851 0.4750 0.2009 0.2804 0.3689 0.1877 0.3261

0.2569 0.2783 0.0599 0.1631 0.2694 0.1300 0.2181 0.2844 0.1039 0.2171

1.3429 1.3059 1.0160 1.0752 1.2905 1.3762 1.5961 1.4912 1.1204 1.4204

1.5995 1.6151 0.3091 0.8027 1.5321 1.5777 1.8410 1.7936 0.8512 1.6241

0.0109 0.0364 0.0036 0.0111 0.0370 0.0037 0.0109 0.0365 0.0036 0.0109

0.0021 0.0066 0.0007 0.0022 0.0070 0.0007 0.0020 0.0069 0.0007 0.0021

25 25 25 25 25 25 25 25 25 25

32 33 34 35 36 37 38 39 40 41

14 14
Scenario number

longRangeErrorDist 

probeRndErrorDist 

Mean[Bi] 

stdDevBi 

Mean[Metric1] 

SD[Metric1] 

Mean[Metric1-Bi] 

SD[Metric1-Bi] 

Mean[ Metric1-Bi/Bi]

SD[ Metric1-Bi/Bi] 

SD[Metric1]/SDBi 

SD[Metric1-Bi]/SDBi

Mean[Metric2] 

SD[Metric2] 

Mean[Metric2-Bi] 

SD[Metric2-Bi] 

Mean[ Metric2-Bi/Bi]

SD[ Metric2-Bi/Bi] 

SD[Metric2]/SDBi 

SD[Metric2-Bi]/SDBi

Mean[Metric3] 

SD[Metric3] 

Mean[Metric3-Bi] 

SD[Metric3-Bi] 

Mean[ Metric3-Bi/Bi]

SD[ Metric3-Bi/Bi] 

SD[Metric3]/SDBi 

SD[Metric3-Bi]/SDBi

Mean[Metric4] 

SD[Metric4] 

Mean[Metric4-Bi] 

SD[Metric4-Bi] 

Mean[ Metric4-Bi/Bi]

SD[ Metric4-Bi/Bi] 

SD[Metric4]/SDBi 

SD[Metric4-Bi]/SDBi

Mean[Metric5] 

SD[Metric5] 

Mean[Metric5-Bi] 

SD[Metric5-Bi] 

Mean[ Metric5-Bi/Bi]

SD[ Metric5-Bi/Bi] 

SD[Metric5]/SDBi 

SD[Metric5-Bi]/SDBi

Mean[Metric6] 

SD[Metric6] 

Mean[Metric6-Bi] 

SD[Metric6-Bi] 

Mean[ Metric6-Bi/Bi]

SD[ Metric6-Bi/Bi] 

SD[Metric6]/SDBi 

SD[Metric6-Bi]/SDBi

Mean[Metric7] 

SD[Metric7] 

Mean[Metric7-Bi] 

SD[Metric7-Bi] 

Mean[ Metric7-Bi/Bi]

SD[ Metric7-Bi/Bi] 

SD[Metric7]/SDBi 

SD[Metric7-Bi]/SDBi

Mean[Metric8] 

SD[Metric8] 

Mean[Metric8-Bi] 

SD[Metric8-Bi] 

Mean[ Metric8-Bi/Bi]

SD[ Metric8-Bi/Bi] 

SD[Metric8]/SDBi 

SD[Metric8-Bi]/SDBi

Mean[Metric9] 

SD[Metric9] 

Mean[Metric9-Bi] 

SD[Metric9-Bi] 

Mean[ Metric9-Bi/Bi]

SD[ Metric9-Bi/Bi] 

SD[Metric9]/SDBi 

SD[Metric9-Bi]/SDBi

formMean 

formStdDev 

Points per sphere

Scenario number

42 43 44 45 46 47 48 49 50 51

N[0.003,0.003] N[0.003,0.010] N[0.003,0.010] N[0.003,0.010] N[0.003,0.001] N[0.003,0.001] N[0.003,0.001] N[0.003,0.003] N[0.003,0.003] N[0.003,0.003]

N[0.0015,0.010] N[0.0015,0.001] N[0.0015,0.003] N[0.0015,0.010] N[0.005,0.001] N[0.005,0.003] N[0.005,0.010] N[0.005,0.001] N[0.005,0.003] N[0.005,0.010]

0.0427 0.0286 0.0319 0.0501 0.0173 0.0240 0.0487 0.0208 0.0261 0.0497

0.0060 0.0048 0.0052 0.0073 0.0008 0.0018 0.0058 0.0015 0.0023 0.0063

0.0441 0.0286 0.0317 0.0512 0.0168 0.0235 0.0501 0.0204 0.0257 0.0508

0.0089 0.0046 0.0050 0.0093 0.0009 0.0027 0.0092 0.0015 0.0027 0.0092

0.0013 0.0000 -0.0002 0.0011 -0.0006 -0.0005 0.0014 -0.0004 -0.0004 0.0011

0.0106 0.0021 0.0039 0.0114 0.0011 0.0032 0.0109 0.0012 0.0034 0.0112

0.0504 0.0056 0.0013 0.0415 -0.0313 -0.0172 0.0431 -0.0176 -0.0074 0.0377

0.2559 0.0797 0.1274 0.2361 0.0610 0.1331 0.2297 0.0590 0.1296 0.2298

1.4871 0.9573 0.9472 1.2844 1.1203 1.4345 1.5815 1.0115 1.1923 1.4741

1.7684 0.4237 0.7486 1.5760 1.3607 1.7318 1.8762 0.8369 1.5036 1.7934

0.0695 0.0302 0.0374 0.0760 0.0189 0.0308 0.0762 0.0223 0.0327 0.0762

0.0008 0.0046 0.0042 0.0027 0.0004 0.0004 0.0007 0.0012 0.0009 0.0009

0.0268 0.0016 0.0055 0.0259 0.0016 0.0068 0.0275 0.0015 0.0067 0.0265

0.0060 0.0019 0.0033 0.0071 0.0008 0.0019 0.0058 0.0009 0.0023 0.0063

0.6577 0.0617 0.1869 0.5471 0.0923 0.2916 0.5876 0.0726 0.2638 0.5574

0.2297 0.0799 0.1273 0.2125 0.0469 0.0976 0.1876 0.0476 0.1054 0.1914

0.1364 0.9411 0.8046 0.3739 0.5089 0.1961 0.1195 0.8405 0.4098 0.1391

1.0065 0.3980 0.6299 0.9747 0.9664 1.0038 1.0028 0.6350 1.0000 1.0049

0.0432 0.0279 0.0310 0.0509 0.0161 0.0209 0.0455 0.0201 0.0239 0.0463

0.0066 0.0048 0.0050 0.0073 0.0008 0.0021 0.0070 0.0015 0.0024 0.0070

0.0005 -0.0006 -0.0009 0.0008 -0.0012 -0.0032 -0.0032 -0.0007 -0.0022 -0.0034

0.0090 0.0013 0.0035 0.0098 0.0010 0.0028 0.0091 0.0012 0.0032 0.0095

0.0317 -0.0211 -0.0227 0.0348 -0.0697 -0.1267 -0.0529 -0.0342 -0.0783 -0.0535

0.2161 0.0467 0.1112 0.1993 0.0567 0.1088 0.1852 0.0575 0.1158 0.1860

1.0988 0.9922 0.9569 1.0004 1.0547 1.1322 1.1958 1.0339 1.0759 1.1173

1.5057 0.2709 0.6746 1.3444 1.2933 1.4884 1.5653 0.8216 1.3936 1.5100

0.0444 0.0281 0.0315 0.0515 0.0164 0.0217 0.0480 0.0203 0.0246 0.0485

0.0060 0.0048 0.0048 0.0067 0.0006 0.0013 0.0056 0.0014 0.0018 0.0055

0.0017 -0.0005 -0.0005 0.0014 -0.0010 -0.0023 -0.0006 -0.0006 -0.0015 -0.0012

0.0086 0.0012 0.0033 0.0093 0.0008 0.0023 0.0081 0.0010 0.0027 0.0084

0.0600 -0.0150 -0.0070 0.0478 -0.0544 -0.0898 0.0008 -0.0251 -0.0508 -0.0089

0.2075 0.0432 0.1031 0.1918 0.0457 0.0879 0.1686 0.0476 0.0975 0.1672

0.9926 0.9879 0.9106 0.9212 0.7122 0.7246 0.9603 0.9369 0.8026 0.8797

1.4296 0.2486 0.6236 1.2783 1.0548 1.2229 1.3927 0.6878 1.1806 1.3344

0.0560 0.0283 0.0331 0.0625 0.0167 0.0241 0.0591 0.0206 0.0267 0.0590

0.0014 0.0048 0.0045 0.0034 0.0005 0.0007 0.0016 0.0014 0.0014 0.0018

0.0133 -0.0002 0.0012 0.0124 -0.0006 0.0000 0.0104 -0.0003 0.0006 0.0093

0.0061 0.0012 0.0031 0.0072 0.0008 0.0020 0.0060 0.0010 0.0024 0.0065

0.3365 -0.0071 0.0472 0.2717 -0.0335 0.0072 0.2305 -0.0120 0.0308 0.2058

0.1849 0.0431 0.1030 0.1777 0.0456 0.0807 0.1484 0.0471 0.0924 0.1527

0.2396 0.9810 0.8593 0.4687 0.6755 0.3816 0.2691 0.9207 0.6024 0.2938

1.0106 0.2471 0.5972 0.9950 1.0397 1.0590 1.0296 0.6764 1.0639 1.0389

0.0606 0.0294 0.0359 0.0690 0.0177 0.0263 0.0639 0.0217 0.0292 0.0645

0.0014 0.0048 0.0046 0.0037 0.0005 0.0006 0.0014 0.0014 0.0013 0.0016

0.0178 0.0008 0.0040 0.0189 0.0004 0.0022 0.0152 0.0008 0.0032 0.0148

0.0061 0.0012 0.0031 0.0072 0.0008 0.0019 0.0059 0.0010 0.0024 0.0064

0.4450 0.0302 0.1371 0.4025 0.0229 0.0993 0.3313 0.0419 0.1285 0.3180

0.2019 0.0446 0.1103 0.1939 0.0459 0.0853 0.1588 0.0470 0.0981 0.1643

0.2291 0.9910 0.8887 0.5051 0.6468 0.3501 0.2376 0.9163 0.5856 0.2624

1.0205 0.2495 0.5935 0.9950 1.0040 1.0332 1.0196 0.6481 1.0492 1.0255

0.0602 0.0320 0.0405 0.0729 0.0193 0.0286 0.0629 0.0234 0.0320 0.0646

0.0085 0.0047 0.0056 0.0098 0.0011 0.0030 0.0095 0.0017 0.0033 0.0096

0.0174 0.0034 0.0086 0.0229 0.0020 0.0046 0.0142 0.0025 0.0060 0.0148

0.0105 0.0021 0.0044 0.0117 0.0012 0.0035 0.0111 0.0014 0.0038 0.0115

0.4359 0.1271 0.2831 0.4835 0.1150 0.1974 0.3106 0.1244 0.2377 0.3191

0.2886 0.0914 0.1645 0.2778 0.0739 0.1526 0.2522 0.0716 0.1572 0.2563

1.4248 0.9737 1.0620 1.3527 1.3951 1.6075 1.6299 1.1487 1.4521 1.5345

1.7527 0.4428 0.8363 1.6057 1.5663 1.8684 1.9102 0.9591 1.6899 1.8387

0.0841 0.0347 0.0484 0.0981 0.0220 0.0366 0.0897 0.0261 0.0401 0.0909

0.0024 0.0046 0.0048 0.0051 0.0005 0.0008 0.0022 0.0014 0.0015 0.0025

0.0414 0.0061 0.0165 0.0480 0.0047 0.0126 0.0410 0.0052 0.0141 0.0412

0.0064 0.0019 0.0034 0.0077 0.0008 0.0020 0.0061 0.0010 0.0025 0.0067

1.0065 0.2251 0.5390 0.9941 0.2726 0.5320 0.8677 0.2531 0.5508 0.8561

0.2826 0.0953 0.1685 0.2760 0.0555 0.1179 0.2235 0.0557 0.1319 0.2321

0.3977 0.9596 0.9205 0.6995 0.6745 0.4267 0.3790 0.9402 0.6833 0.3989

1.0693 0.3999 0.6471 1.0658 1.0135 1.0560 1.0547 0.6535 1.0882 1.0641

0.0588 0.0314 0.0398 0.0713 0.0193 0.0286 0.0626 0.0234 0.0320 0.0643

0.0088 0.0049 0.0057 0.0100 0.0011 0.0030 0.0097 0.0017 0.0033 0.0099

0.0161 0.0028 0.0079 0.0212 0.0020 0.0046 0.0139 0.0025 0.0060 0.0146

0.0107 0.0015 0.0041 0.0118 0.0012 0.0035 0.0114 0.0014 0.0038 0.0117

0.4043 0.1013 0.2610 0.4490 0.1150 0.1974 0.3047 0.1243 0.2375 0.3136

0.2884 0.0585 0.1508 0.2765 0.0739 0.1526 0.2561 0.0716 0.1573 0.2598

1.4644 1.0095 1.0824 1.3795 1.3951 1.6075 1.6719 1.1482 1.4540 1.5743

1.7825 0.3071 0.7899 1.6204 1.5663 1.8684 1.9504 0.9584 1.6914 1.8729

0.0366 0.0037 0.0110 0.0365 0.0036 0.0110 0.0368 0.0036 0.0109 0.0364

0.0068 0.0007 0.0021 0.0073 0.0007 0.0021 0.0069 0.0007 0.0021 0.0067

25 25 25 25 25 25 25 25 25 25

42 43 44 45 46 47 48 49 50 51

15 15
Scenario number

longRangeErrorDist 

probeRndErrorDist 

Mean[Bi] 

stdDevBi 

Mean[Metric1] 

SD[Metric1] 

Mean[Metric1-Bi] 

SD[Metric1-Bi] 

Mean[ Metric1-Bi/Bi]

SD[ Metric1-Bi/Bi] 

SD[Metric1]/SDBi 

SD[Metric1-Bi]/SDBi

Mean[Metric2] 

SD[Metric2] 

Mean[Metric2-Bi] 

SD[Metric2-Bi] 

Mean[ Metric2-Bi/Bi]

SD[ Metric2-Bi/Bi] 

SD[Metric2]/SDBi 

SD[Metric2-Bi]/SDBi

Mean[Metric3] 

SD[Metric3] 

Mean[Metric3-Bi] 

SD[Metric3-Bi] 

Mean[ Metric3-Bi/Bi]

SD[ Metric3-Bi/Bi] 

SD[Metric3]/SDBi 

SD[Metric3-Bi]/SDBi

Mean[Metric4] 

SD[Metric4] 

Mean[Metric4-Bi] 

SD[Metric4-Bi] 

Mean[ Metric4-Bi/Bi]

SD[ Metric4-Bi/Bi] 

SD[Metric4]/SDBi 

SD[Metric4-Bi]/SDBi

Mean[Metric5] 

SD[Metric5] 

Mean[Metric5-Bi] 

SD[Metric5-Bi] 

Mean[ Metric5-Bi/Bi]

SD[ Metric5-Bi/Bi] 

SD[Metric5]/SDBi 

SD[Metric5-Bi]/SDBi

Mean[Metric6] 

SD[Metric6] 

Mean[Metric6-Bi] 

SD[Metric6-Bi] 

Mean[ Metric6-Bi/Bi]

SD[ Metric6-Bi/Bi] 

SD[Metric6]/SDBi 

SD[Metric6-Bi]/SDBi

Mean[Metric7] 

SD[Metric7] 

Mean[Metric7-Bi] 

SD[Metric7-Bi] 

Mean[ Metric7-Bi/Bi]

SD[ Metric7-Bi/Bi] 

SD[Metric7]/SDBi 

SD[Metric7-Bi]/SDBi

Mean[Metric8] 

SD[Metric8] 

Mean[Metric8-Bi] 

SD[Metric8-Bi] 

Mean[ Metric8-Bi/Bi]

SD[ Metric8-Bi/Bi] 

SD[Metric8]/SDBi 

SD[Metric8-Bi]/SDBi

Mean[Metric9] 

SD[Metric9] 

Mean[Metric9-Bi] 

SD[Metric9-Bi] 

Mean[ Metric9-Bi/Bi]

SD[ Metric9-Bi/Bi] 

SD[Metric9]/SDBi 

SD[Metric9-Bi]/SDBi

formMean 

formStdDev 

Points per sphere

Scenario number

52 53 54 55 56 57 58 59 60 61

N[0.003,0.010] N[0.003,0.010] N[0.003,0.010] N[0.010,0.001] N[0.010,0.001] N[0.010,0.001] N[0.010,0.003] N[0.010,0.003] N[0.010,0.003] N[0.010,0.010]

N[0.005,0.001] N[0.005,0.003] N[0.005,0.010] N[0.,0.001] N[0.,0.003] N[0.,0.010] N[0.,0.001] N[0.,0.003] N[0.,0.010] N[0.,0.001]

0.0354 0.0386 0.0565 0.0143 0.0210 0.0461 0.0179 0.0230 0.0467 0.0327

0.0048 0.0052 0.0080 0.0008 0.0019 0.0062 0.0015 0.0023 0.0064 0.0047

0.0355 0.0385 0.0585 0.0132 0.0183 0.0431 0.0172 0.0210 0.0447 0.0320

0.0045 0.0050 0.0093 0.0009 0.0024 0.0092 0.0016 0.0027 0.0088 0.0047

0.0001 -0.0001 0.0020 -0.0011 -0.0027 -0.0030 -0.0007 -0.0020 -0.0020 -0.0007

0.0025 0.0040 0.0120 0.0011 0.0031 0.0109 0.0012 0.0033 0.0108 0.0013

0.0075 0.0048 0.0551 -0.0782 -0.1224 -0.0487 -0.0377 -0.0804 -0.0255 -0.0213

0.0832 0.1095 0.2168 0.0725 0.1384 0.2344 0.0644 0.1399 0.2295 0.0402

0.9497 0.9472 1.1655 1.1405 1.2317 1.4700 1.0670 1.1673 1.3869 1.0079

0.5318 0.7699 1.4919 1.4136 1.5762 1.7557 0.7719 1.4400 1.7000 0.2751

0.0370 0.0442 0.0828 0.0150 0.0248 0.0689 0.0189 0.0278 0.0699 0.0335

0.0044 0.0042 0.0027 0.0005 0.0005 0.0010 0.0014 0.0012 0.0012 0.0046

0.0016 0.0056 0.0263 0.0007 0.0038 0.0228 0.0010 0.0048 0.0232 0.0009

0.0024 0.0035 0.0079 0.0008 0.0020 0.0063 0.0010 0.0023 0.0064 0.0011

0.0505 0.1566 0.4926 0.0499 0.1905 0.5219 0.0580 0.2176 0.5234 0.0277

0.0826 0.1081 0.2009 0.0551 0.1098 0.1996 0.0563 0.1142 0.1990 0.0352

0.9313 0.8005 0.3320 0.6456 0.2746 0.1566 0.9509 0.5127 0.1834 0.9841

0.5094 0.6613 0.9872 1.0116 1.0417 1.0090 0.6403 0.9908 1.0150 0.2345

0.0347 0.0372 0.0551 0.0132 0.0183 0.0437 0.0172 0.0211 0.0451 0.0320

0.0048 0.0052 0.0079 0.0008 0.0021 0.0070 0.0016 0.0025 0.0070 0.0047

-0.0007 -0.0014 -0.0013 -0.0011 -0.0027 -0.0024 -0.0007 -0.0020 -0.0016 -0.0007

0.0013 0.0034 0.0107 0.0011 0.0028 0.0092 0.0012 0.0031 0.0093 0.0013

-0.0195 -0.0326 -0.0068 -0.0779 -0.1209 -0.0349 -0.0376 -0.0783 -0.0180 -0.0213

0.0364 0.0888 0.1881 0.0712 0.1263 0.1967 0.0639 0.1315 0.1975 0.0399

1.0030 0.9985 0.9880 1.1137 1.0735 1.1199 1.0626 1.0667 1.1003 1.0083

0.2668 0.6557 1.3339 1.3912 1.4524 1.4810 0.7664 1.3614 1.4717 0.2738

0.0349 0.0378 0.0568 0.0135 0.0192 0.0460 0.0174 0.0218 0.0470 0.0321

0.0047 0.0049 0.0065 0.0006 0.0014 0.0059 0.0015 0.0017 0.0060 0.0046

-0.0005 -0.0008 0.0004 -0.0008 -0.0018 -0.0001 -0.0005 -0.0012 0.0003 -0.0005

0.0011 0.0031 0.0094 0.0009 0.0023 0.0085 0.0010 0.0026 0.0086 0.0012

-0.0132 -0.0157 0.0232 -0.0562 -0.0791 0.0158 -0.0236 -0.0438 0.0240 -0.0155

0.0325 0.0798 0.1687 0.0565 0.1033 0.1855 0.0570 0.1087 0.1851 0.0354

0.9904 0.9283 0.8113 0.7441 0.7238 0.9524 0.9778 0.7501 0.9486 0.9888

0.2385 0.5911 1.1711 1.1186 1.1935 1.3705 0.6811 1.1351 1.3590 0.2447

0.0351 0.0392 0.0667 0.0139 0.0217 0.0577 0.0178 0.0241 0.0587 0.0323

0.0047 0.0047 0.0038 0.0005 0.0007 0.0015 0.0014 0.0012 0.0016 0.0046

-0.0003 0.0006 0.0102 -0.0004 0.0007 0.0116 -0.0001 0.0011 0.0121 -0.0003

0.0011 0.0030 0.0080 0.0008 0.0021 0.0064 0.0010 0.0023 0.0066 0.0011

-0.0083 0.0203 0.2015 -0.0264 0.0415 0.2729 -0.0049 0.0568 0.2807 -0.0095

0.0324 0.0803 0.1630 0.0543 0.0983 0.1684 0.0564 0.1024 0.1700 0.0352

0.9853 0.8919 0.4704 0.6753 0.3580 0.2377 0.9574 0.5296 0.2496 0.9831

0.2378 0.5789 0.9937 1.0578 1.0536 1.0227 0.6674 1.0093 1.0351 0.2433

0.0361 0.0422 0.0736 0.0149 0.0238 0.0623 0.0188 0.0269 0.0636 0.0335

0.0047 0.0047 0.0038 0.0005 0.0006 0.0014 0.0014 0.0013 0.0016 0.0046

0.0007 0.0036 0.0172 0.0006 0.0028 0.0162 0.0009 0.0039 0.0169 0.0008

0.0011 0.0028 0.0080 0.0008 0.0020 0.0063 0.0010 0.0023 0.0065 0.0011

0.0212 0.1002 0.3270 0.0437 0.1410 0.3757 0.0550 0.1793 0.3861 0.0269

0.0315 0.0817 0.1798 0.0550 0.1063 0.1816 0.0563 0.1117 0.1826 0.0352

0.9911 0.8965 0.4720 0.6536 0.3056 0.2169 0.9563 0.5533 0.2470 0.9859

0.2267 0.5450 1.0025 1.0143 1.0508 1.0191 0.6418 1.0012 1.0276 0.2353

0.0389 0.0472 0.0781 0.0169 0.0271 0.0648 0.0210 0.0306 0.0666 0.0360

0.0047 0.0056 0.0108 0.0010 0.0024 0.0083 0.0017 0.0028 0.0086 0.0047

0.0035 0.0086 0.0216 0.0025 0.0060 0.0187 0.0031 0.0076 0.0199 0.0033

0.0027 0.0044 0.0129 0.0012 0.0030 0.0103 0.0013 0.0034 0.0105 0.0014

0.1036 0.2323 0.4077 0.1801 0.2972 0.4293 0.1764 0.3409 0.4511 0.1038

0.0922 0.1344 0.2644 0.0869 0.1609 0.2596 0.0755 0.1660 0.2618 0.0474

0.9776 1.0642 1.3495 1.2773 1.2425 1.3325 1.1036 1.2137 1.3470 1.0076

0.5586 0.8466 1.6136 1.5362 1.5609 1.6500 0.8301 1.4516 1.6478 0.2925

0.0415 0.0552 0.1048 0.0191 0.0335 0.0869 0.0232 0.0374 0.0889 0.0382

0.0045 0.0048 0.0049 0.0005 0.0008 0.0023 0.0015 0.0015 0.0026 0.0047

0.0061 0.0166 0.0483 0.0048 0.0124 0.0409 0.0053 0.0144 0.0422 0.0055

0.0024 0.0035 0.0085 0.0008 0.0021 0.0066 0.0010 0.0024 0.0068 0.0011

0.1795 0.4441 0.8889 0.3355 0.6049 0.9193 0.2998 0.6378 0.9373 0.1735

0.0920 0.1357 0.2573 0.0683 0.1485 0.2548 0.0680 0.1533 0.2568 0.0452

0.9497 0.9147 0.6140 0.6937 0.3926 0.3660 0.9915 0.6674 0.4100 0.9967

0.5122 0.6785 1.0647 1.0288 1.0806 1.0585 0.6522 1.0385 1.0764 0.2355

0.0381 0.0464 0.0773 0.0163 0.0255 0.0597 0.0204 0.0288 0.0620 0.0354

0.0049 0.0058 0.0110 0.0011 0.0029 0.0096 0.0018 0.0033 0.0096 0.0048

0.0027 0.0079 0.0208 0.0020 0.0045 0.0136 0.0026 0.0058 0.0153 0.0028

0.0015 0.0040 0.0130 0.0013 0.0035 0.0112 0.0014 0.0038 0.0114 0.0015

0.0788 0.2106 0.3920 0.1406 0.2235 0.3180 0.1454 0.2618 0.3505 0.0866

0.0441 0.1150 0.2633 0.0950 0.1757 0.2686 0.0803 0.1804 0.2716 0.0483

1.0228 1.1054 1.3740 1.4637 1.5019 1.5360 1.1669 1.4445 1.5093 1.0241

0.3045 0.7579 1.6214 1.7150 1.7805 1.8056 0.9033 1.6555 1.7974 0.3100

0.0036 0.0110 0.0370 0.0037 0.0110 0.0365 0.0037 0.0110 0.0368 0.0037

0.0007 0.0020 0.0070 0.0007 0.0020 0.0070 0.0007 0.0021 0.0072 0.0007

25 25 25 25 25 25 25 25 25 25

52 53 54 55 56 57 58 59 60 61

16 16
Scenario number

longRangeErrorDist 

probeRndErrorDist 

Mean[Bi] 

stdDevBi 

Mean[Metric1] 

SD[Metric1] 

Mean[Metric1-Bi] 

SD[Metric1-Bi] 

Mean[ Metric1-Bi/Bi]

SD[ Metric1-Bi/Bi] 

SD[Metric1]/SDBi 

SD[Metric1-Bi]/SDBi

Mean[Metric2] 

SD[Metric2] 

Mean[Metric2-Bi] 

SD[Metric2-Bi] 

Mean[ Metric2-Bi/Bi]

SD[ Metric2-Bi/Bi] 

SD[Metric2]/SDBi 

SD[Metric2-Bi]/SDBi

Mean[Metric3] 

SD[Metric3] 

Mean[Metric3-Bi] 

SD[Metric3-Bi] 

Mean[ Metric3-Bi/Bi]

SD[ Metric3-Bi/Bi] 

SD[Metric3]/SDBi 

SD[Metric3-Bi]/SDBi

Mean[Metric4] 

SD[Metric4] 

Mean[Metric4-Bi] 

SD[Metric4-Bi] 

Mean[ Metric4-Bi/Bi]

SD[ Metric4-Bi/Bi] 

SD[Metric4]/SDBi 

SD[Metric4-Bi]/SDBi

Mean[Metric5] 

SD[Metric5] 

Mean[Metric5-Bi] 

SD[Metric5-Bi] 

Mean[ Metric5-Bi/Bi]

SD[ Metric5-Bi/Bi] 

SD[Metric5]/SDBi 

SD[Metric5-Bi]/SDBi

Mean[Metric6] 

SD[Metric6] 

Mean[Metric6-Bi] 

SD[Metric6-Bi] 

Mean[ Metric6-Bi/Bi]

SD[ Metric6-Bi/Bi] 

SD[Metric6]/SDBi 

SD[Metric6-Bi]/SDBi

Mean[Metric7] 

SD[Metric7] 

Mean[Metric7-Bi] 

SD[Metric7-Bi] 

Mean[ Metric7-Bi/Bi]

SD[ Metric7-Bi/Bi] 

SD[Metric7]/SDBi 

SD[Metric7-Bi]/SDBi

Mean[Metric8] 

SD[Metric8] 

Mean[Metric8-Bi] 

SD[Metric8-Bi] 

Mean[ Metric8-Bi/Bi]

SD[ Metric8-Bi/Bi] 

SD[Metric8]/SDBi 

SD[Metric8-Bi]/SDBi

Mean[Metric9] 

SD[Metric9] 

Mean[Metric9-Bi] 

SD[Metric9-Bi] 

Mean[ Metric9-Bi/Bi]

SD[ Metric9-Bi/Bi] 

SD[Metric9]/SDBi 

SD[Metric9-Bi]/SDBi

formMean 

formStdDev 

Points per sphere

Scenario number

62 63 64 65 66 67 68 69 70 71

N[0.010,0.010] N[0.010,0.010] N[0.010,0.001] N[0.010,0.001] N[0.010,0.001] N[0.010,0.003] N[0.010,0.003] N[0.010,0.003] N[0.010,0.010] N[0.010,0.010]

N[0.,0.003] N[0.,0.010] N[0.0015,0.001] N[0.0015,0.003] N[0.0015,0.010] N[0.0015,0.001] N[0.0015,0.003] N[0.0015,0.010] N[0.0015,0.001] N[0.0015,0.003]

0.0359 0.0535 0.0174 0.0240 0.0491 0.0210 0.0261 0.0495 0.0354 0.0384

0.0051 0.0074 0.0008 0.0018 0.0063 0.0016 0.0023 0.0062 0.0049 0.0050

0.0346 0.0524 0.0163 0.0213 0.0464 0.0203 0.0242 0.0477 0.0348 0.0372

0.0051 0.0090 0.0009 0.0024 0.0089 0.0016 0.0027 0.0089 0.0050 0.0051

-0.0013 -0.0010 -0.0011 -0.0026 -0.0027 -0.0007 -0.0019 -0.0018 -0.0006 -0.0012

0.0036 0.0111 0.0011 0.0030 0.0110 0.0012 0.0034 0.0107 0.0013 0.0035

-0.0312 -0.0031 -0.0612 -0.1038 -0.0385 -0.0306 -0.0664 -0.0226 -0.0171 -0.0270

0.1013 0.2079 0.0590 0.1218 0.2239 0.0561 0.1233 0.2171 0.0369 0.0897

0.9935 1.2049 1.1470 1.3109 1.3992 1.0164 1.1683 1.4237 1.0091 1.0220

0.7158 1.4985 1.3980 1.6567 1.7381 0.7619 1.4284 1.7094 0.2598 0.7053

0.0401 0.0752 0.0180 0.0279 0.0714 0.0219 0.0306 0.0724 0.0363 0.0427

0.0044 0.0032 0.0005 0.0006 0.0009 0.0014 0.0012 0.0011 0.0049 0.0044

0.0041 0.0217 0.0007 0.0040 0.0223 0.0010 0.0045 0.0229 0.0009 0.0043

0.0030 0.0073 0.0008 0.0019 0.0064 0.0010 0.0023 0.0063 0.0011 0.0028

0.1236 0.4308 0.0402 0.1730 0.4783 0.0473 0.1822 0.4846 0.0262 0.1186

0.0936 0.1883 0.0447 0.0891 0.1847 0.0477 0.1002 0.1815 0.0321 0.0797

0.8681 0.4271 0.6516 0.3001 0.1434 0.9185 0.5109 0.1778 0.9903 0.8785

0.5919 0.9781 1.0093 1.0306 1.0110 0.6243 0.9963 1.0153 0.2205 0.5605

0.0346 0.0529 0.0162 0.0208 0.0455 0.0202 0.0238 0.0467 0.0347 0.0371

0.0050 0.0075 0.0009 0.0021 0.0069 0.0016 0.0025 0.0069 0.0050 0.0051

-0.0013 -0.0006 -0.0012 -0.0031 -0.0036 -0.0007 -0.0023 -0.0029 -0.0006 -0.0013

0.0036 0.0099 0.0010 0.0028 0.0095 0.0012 0.0032 0.0091 0.0013 0.0034

-0.0308 0.0057 -0.0670 -0.1252 -0.0587 -0.0334 -0.0809 -0.0438 -0.0179 -0.0315

0.0992 0.1853 0.0579 0.1101 0.1881 0.0556 0.1155 0.1814 0.0365 0.0878

0.9822 1.0040 1.1225 1.1435 1.0893 1.0171 1.0803 1.1023 1.0107 1.0201

0.7036 1.3340 1.3758 1.5246 1.4944 0.7571 1.3541 1.4618 0.2573 0.6925

0.0352 0.0543 0.0164 0.0218 0.0478 0.0204 0.0246 0.0487 0.0349 0.0376

0.0047 0.0064 0.0006 0.0014 0.0057 0.0015 0.0017 0.0055 0.0049 0.0046

-0.0008 0.0008 -0.0009 -0.0022 -0.0013 -0.0006 -0.0015 -0.0009 -0.0005 -0.0008

0.0033 0.0089 0.0008 0.0023 0.0084 0.0010 0.0026 0.0081 0.0011 0.0030

-0.0161 0.0315 -0.0525 -0.0849 -0.0118 -0.0253 -0.0517 -0.0031 -0.0130 -0.0170

0.0889 0.1693 0.0443 0.0907 0.1690 0.0480 0.0933 0.1614 0.0328 0.0762

0.9297 0.8595 0.7588 0.7418 0.8955 0.9683 0.7269 0.8815 0.9984 0.9280

0.6382 1.2010 1.0695 1.2695 1.3307 0.6573 1.1059 1.2934 0.2324 0.6018

0.0367 0.0641 0.0168 0.0240 0.0590 0.0207 0.0266 0.0594 0.0351 0.0390

0.0045 0.0036 0.0005 0.0008 0.0015 0.0015 0.0013 0.0016 0.0049 0.0044

0.0008 0.0106 -0.0006 0.0001 0.0099 -0.0003 0.0005 0.0099 -0.0003 0.0006

0.0031 0.0074 0.0008 0.0020 0.0064 0.0010 0.0024 0.0064 0.0011 0.0029

0.0272 0.2178 -0.0323 0.0095 0.2204 -0.0125 0.0266 0.2182 -0.0079 0.0203

0.0875 0.1630 0.0438 0.0820 0.1534 0.0473 0.0904 0.1514 0.0326 0.0754

0.8880 0.4812 0.7154 0.4241 0.2384 0.9467 0.5646 0.2584 0.9932 0.8875

0.6123 0.9997 1.0437 1.0865 1.0170 0.6443 1.0234 1.0307 0.2310 0.5799

0.0397 0.0708 0.0178 0.0263 0.0638 0.0218 0.0293 0.0649 0.0362 0.0421

0.0045 0.0037 0.0005 0.0006 0.0013 0.0015 0.0013 0.0016 0.0049 0.0045

0.0038 0.0173 0.0004 0.0023 0.0147 0.0008 0.0032 0.0154 0.0008 0.0037

0.0030 0.0074 0.0008 0.0019 0.0065 0.0010 0.0024 0.0064 0.0011 0.0028

0.1133 0.3452 0.0264 0.1037 0.3199 0.0405 0.1317 0.3309 0.0244 0.1026

0.0927 0.1783 0.0445 0.0852 0.1664 0.0477 0.0975 0.1646 0.0318 0.0780

0.8847 0.5020 0.6721 0.3527 0.2081 0.9316 0.5685 0.2513 0.9942 0.9053

0.5943 0.9926 1.0164 1.0445 1.0224 0.6271 1.0119 1.0309 0.2197 0.5619

0.0453 0.0787 0.0194 0.0286 0.0652 0.0235 0.0322 0.0672 0.0382 0.0464

0.0054 0.0096 0.0011 0.0029 0.0084 0.0018 0.0033 0.0083 0.0051 0.0056

0.0094 0.0252 0.0021 0.0047 0.0161 0.0026 0.0061 0.0177 0.0028 0.0080

0.0040 0.0111 0.0013 0.0034 0.0107 0.0014 0.0037 0.0103 0.0015 0.0041

0.2719 0.4952 0.1211 0.2027 0.3504 0.1244 0.2400 0.3783 0.0822 0.2153

0.1296 0.2502 0.0748 0.1516 0.2472 0.0685 0.1529 0.2398 0.0447 0.1147

1.0552 1.2860 1.4716 1.5567 1.3277 1.1321 1.3880 1.3359 1.0286 1.1352

0.7828 1.4882 1.6655 1.8702 1.6830 0.8786 1.5918 1.6504 0.2988 0.8170

0.0519 0.0999 0.0221 0.0366 0.0894 0.0261 0.0402 0.0913 0.0409 0.0545

0.0049 0.0052 0.0005 0.0008 0.0021 0.0015 0.0015 0.0024 0.0050 0.0048

0.0160 0.0464 0.0048 0.0126 0.0403 0.0052 0.0141 0.0418 0.0056 0.0160

0.0031 0.0079 0.0008 0.0020 0.0067 0.0010 0.0024 0.0067 0.0011 0.0029

0.4578 0.9001 0.2766 0.5364 0.8504 0.2500 0.5521 0.8719 0.1608 0.4279

0.1248 0.2519 0.0536 0.1174 0.2344 0.0564 0.1314 0.2326 0.0402 0.1047

0.9564 0.7024 0.7008 0.4289 0.3379 0.9560 0.6602 0.3927 1.0030 0.9680

0.6081 1.0592 1.0270 1.0691 1.0568 0.6330 1.0431 1.0743 0.2218 0.5763

0.0438 0.0742 0.0194 0.0286 0.0628 0.0235 0.0320 0.0648 0.0382 0.0463

0.0056 0.0104 0.0011 0.0029 0.0096 0.0018 0.0034 0.0096 0.0051 0.0057

0.0079 0.0207 0.0021 0.0046 0.0137 0.0026 0.0059 0.0153 0.0028 0.0079

0.0042 0.0120 0.0013 0.0035 0.0116 0.0014 0.0038 0.0113 0.0015 0.0041

0.2282 0.4103 0.1211 0.1992 0.2994 0.1244 0.2352 0.3277 0.0819 0.2129

0.1321 0.2585 0.0748 0.1540 0.2615 0.0685 0.1569 0.2537 0.0443 0.1157

1.0955 1.3945 1.4716 1.6017 1.5098 1.1321 1.4398 1.5414 1.0293 1.1458

0.8280 1.6187 1.6655 1.9053 1.8328 0.8786 1.6403 1.8094 0.2971 0.8279

0.0111 0.0366 0.0037 0.0110 0.0366 0.0036 0.0110 0.0367 0.0037 0.0110

0.0021 0.0068 0.0007 0.0020 0.0070 0.0007 0.0020 0.0068 0.0007 0.0021

25 25 25 25 25 25 25 25 25 25

62 63 64 65 66 67 68 69 70 71

17 17
Scenario number

longRangeErrorDist 

probeRndErrorDist 

Mean[Bi] 

stdDevBi 

Mean[Metric1] 

SD[Metric1] 

Mean[Metric1-Bi] 

SD[Metric1-Bi] 

Mean[ Metric1-Bi/Bi]

SD[ Metric1-Bi/Bi] 

SD[Metric1]/SDBi 

SD[Metric1-Bi]/SDBi

Mean[Metric2] 

SD[Metric2] 

Mean[Metric2-Bi] 

SD[Metric2-Bi] 

Mean[ Metric2-Bi/Bi]

SD[ Metric2-Bi/Bi] 

SD[Metric2]/SDBi 

SD[Metric2-Bi]/SDBi

Mean[Metric3] 

SD[Metric3] 

Mean[Metric3-Bi] 

SD[Metric3-Bi] 

Mean[ Metric3-Bi/Bi]

SD[ Metric3-Bi/Bi] 

SD[Metric3]/SDBi 

SD[Metric3-Bi]/SDBi

Mean[Metric4] 

SD[Metric4] 

Mean[Metric4-Bi] 

SD[Metric4-Bi] 

Mean[ Metric4-Bi/Bi]

SD[ Metric4-Bi/Bi] 

SD[Metric4]/SDBi 

SD[Metric4-Bi]/SDBi

Mean[Metric5] 

SD[Metric5] 

Mean[Metric5-Bi] 

SD[Metric5-Bi] 

Mean[ Metric5-Bi/Bi]

SD[ Metric5-Bi/Bi] 

SD[Metric5]/SDBi 

SD[Metric5-Bi]/SDBi

Mean[Metric6] 

SD[Metric6] 

Mean[Metric6-Bi] 

SD[Metric6-Bi] 

Mean[ Metric6-Bi/Bi]

SD[ Metric6-Bi/Bi] 

SD[Metric6]/SDBi 

SD[Metric6-Bi]/SDBi

Mean[Metric7] 

SD[Metric7] 

Mean[Metric7-Bi] 

SD[Metric7-Bi] 

Mean[ Metric7-Bi/Bi]

SD[ Metric7-Bi/Bi] 

SD[Metric7]/SDBi 

SD[Metric7-Bi]/SDBi

Mean[Metric8] 

SD[Metric8] 

Mean[Metric8-Bi] 

SD[Metric8-Bi] 

Mean[ Metric8-Bi/Bi]

SD[ Metric8-Bi/Bi] 

SD[Metric8]/SDBi 

SD[Metric8-Bi]/SDBi

Mean[Metric9] 

SD[Metric9] 

Mean[Metric9-Bi] 

SD[Metric9-Bi] 

Mean[ Metric9-Bi/Bi]

SD[ Metric9-Bi/Bi] 

SD[Metric9]/SDBi 

SD[Metric9-Bi]/SDBi

formMean 

formStdDev 

Points per sphere

Scenario number

72 73 74 75 76 77 78 79 80 81

N[0.010,0.010] N[0.010,0.001] N[0.010,0.001] N[0.010,0.001] N[0.010,0.003] N[0.010,0.003] N[0.010,0.003] N[0.010,0.010] N[0.010,0.010] N[0.010,0.010]

N[0.0015,0.010] N[0.005,0.001] N[0.005,0.003] N[0.005,0.010] N[0.005,0.001] N[0.005,0.003] N[0.005,0.010] N[0.005,0.001] N[0.005,0.003] N[0.005,0.010]

0.0568 0.0243 0.0311 0.0560 0.0280 0.0330 0.0564 0.0424 0.0456 0.0636

0.0078 0.0007 0.0019 0.0060 0.0015 0.0022 0.0064 0.0050 0.0050 0.0079

0.0553 0.0232 0.0282 0.0534 0.0273 0.0311 0.0543 0.0417 0.0443 0.0618

0.0092 0.0009 0.0024 0.0086 0.0015 0.0026 0.0087 0.0050 0.0051 0.0089

-0.0015 -0.0011 -0.0029 -0.0026 -0.0007 -0.0019 -0.0021 -0.0007 -0.0013 -0.0018

0.0114 0.0011 0.0031 0.0104 0.0011 0.0031 0.0109 0.0012 0.0037 0.0110

-0.0118 -0.0443 -0.0897 -0.0357 -0.0249 -0.0533 -0.0255 -0.0165 -0.0268 -0.0158

0.2026 0.0430 0.0944 0.1823 0.0401 0.0907 0.1909 0.0293 0.0803 0.1719

1.1787 1.1663 1.2748 1.4351 0.9699 1.1870 1.3516 0.9913 1.0208 1.1323

1.4661 1.4556 1.6339 1.7414 0.7387 1.4219 1.7080 0.2492 0.7366 1.4048

0.0787 0.0250 0.0347 0.0778 0.0288 0.0372 0.0789 0.0432 0.0497 0.0847

0.0032 0.0005 0.0005 0.0009 0.0014 0.0012 0.0012 0.0049 0.0045 0.0032

0.0218 0.0007 0.0036 0.0218 0.0009 0.0042 0.0225 0.0008 0.0041 0.0211

0.0075 0.0008 0.0019 0.0060 0.0010 0.0022 0.0065 0.0011 0.0030 0.0076

0.4071 0.0290 0.1197 0.4056 0.0323 0.1312 0.4160 0.0190 0.0939 0.3493

0.1768 0.0324 0.0676 0.1468 0.0351 0.0721 0.1554 0.0256 0.0699 0.1536

0.4096 0.6598 0.2896 0.1496 0.8796 0.5712 0.1825 0.9864 0.8956 0.4123

0.9577 1.0598 1.0369 1.0071 0.6261 1.0075 1.0075 0.2119 0.5932 0.9664

0.0548 0.0230 0.0269 0.0497 0.0271 0.0302 0.0509 0.0417 0.0438 0.0595

0.0078 0.0008 0.0021 0.0067 0.0015 0.0024 0.0068 0.0050 0.0052 0.0078

-0.0020 -0.0013 -0.0042 -0.0063 -0.0009 -0.0028 -0.0055 -0.0008 -0.0018 -0.0040

0.0103 0.0011 0.0028 0.0090 0.0011 0.0029 0.0095 0.0012 0.0036 0.0101

-0.0206 -0.0539 -0.1324 -0.1024 -0.0304 -0.0833 -0.0868 -0.0180 -0.0368 -0.0523

0.1805 0.0421 0.0853 0.1507 0.0398 0.0853 0.1593 0.0293 0.0790 0.1536

1.0024 1.1460 1.1244 1.1213 0.9783 1.1220 1.0622 0.9961 1.0310 0.9910

1.3179 1.4321 1.5136 1.4962 0.7356 1.3575 1.4765 0.2490 0.7284 1.2843

0.0566 0.0232 0.0280 0.0527 0.0273 0.0310 0.0536 0.0419 0.0445 0.0620

0.0064 0.0005 0.0012 0.0052 0.0014 0.0018 0.0052 0.0050 0.0049 0.0061

-0.0002 -0.0011 -0.0030 -0.0032 -0.0007 -0.0020 -0.0028 -0.0006 -0.0012 -0.0016

0.0092 0.0008 0.0022 0.0079 0.0010 0.0025 0.0081 0.0011 0.0032 0.0090

0.0119 -0.0439 -0.0949 -0.0471 -0.0246 -0.0584 -0.0386 -0.0132 -0.0232 -0.0125

0.1619 0.0321 0.0661 0.1343 0.0349 0.0716 0.1388 0.0260 0.0682 0.1381

0.8171 0.7462 0.6323 0.8676 0.9185 0.8339 0.8163 0.9955 0.9704 0.7766

1.1768 1.1064 1.1937 1.3121 0.6505 1.1493 1.2697 0.2213 0.6329 1.1443

0.0663 0.0235 0.0297 0.0627 0.0275 0.0326 0.0635 0.0420 0.0456 0.0707

0.0037 0.0005 0.0009 0.0017 0.0014 0.0015 0.0020 0.0050 0.0047 0.0040

0.0095 -0.0008 -0.0013 0.0068 -0.0005 -0.0004 0.0070 -0.0004 0.0000 0.0072

0.0077 0.0008 0.0020 0.0062 0.0010 0.0023 0.0066 0.0011 0.0031 0.0079

0.1866 -0.0335 -0.0399 0.1338 -0.0173 -0.0096 0.1383 -0.0099 0.0029 0.1268

0.1537 0.0318 0.0625 0.1212 0.0349 0.0689 0.1279 0.0260 0.0682 0.1327

0.4751 0.7272 0.4572 0.2813 0.9116 0.7137 0.3195 0.9931 0.9435 0.5117

0.9933 1.0888 1.0956 1.0321 0.6469 1.0731 1.0328 0.2210 0.6249 1.0006

0.0732 0.0246 0.0320 0.0677 0.0286 0.0352 0.0693 0.0431 0.0487 0.0776

0.0039 0.0005 0.0007 0.0014 0.0014 0.0014 0.0018 0.0050 0.0047 0.0041

0.0164 0.0002 0.0010 0.0118 0.0006 0.0022 0.0128 0.0007 0.0031 0.0140

0.0076 0.0008 0.0020 0.0061 0.0010 0.0023 0.0066 0.0011 0.0030 0.0078

0.3096 0.0105 0.0353 0.2241 0.0219 0.0690 0.2427 0.0161 0.0716 0.2356

0.1655 0.0324 0.0642 0.1292 0.0350 0.0706 0.1382 0.0254 0.0689 0.1429

0.4958 0.6949 0.3647 0.2381 0.9027 0.6664 0.2785 0.9937 0.9382 0.5269

0.9711 1.0742 1.0592 1.0211 0.6302 1.0394 1.0248 0.2117 0.6012 0.9888

0.0793 0.0264 0.0354 0.0699 0.0305 0.0389 0.0717 0.0451 0.0534 0.0833

0.0097 0.0011 0.0029 0.0091 0.0016 0.0032 0.0092 0.0050 0.0057 0.0103

0.0225 0.0020 0.0043 0.0139 0.0025 0.0059 0.0152 0.0027 0.0078 0.0198

0.0115 0.0013 0.0035 0.0109 0.0013 0.0036 0.0113 0.0014 0.0041 0.0120

0.4183 0.0844 0.1425 0.2622 0.0919 0.1818 0.2861 0.0647 0.1748 0.3267

0.2390 0.0538 0.1154 0.2071 0.0484 0.1141 0.2186 0.0355 0.0983 0.2108

1.2514 1.4923 1.5309 1.5230 1.0620 1.4800 1.4422 1.0002 1.1315 1.3174

1.4757 1.7438 1.8490 1.8113 0.8435 1.6617 1.7645 0.2824 0.8264 1.5252

0.1034 0.0291 0.0432 0.0956 0.0331 0.0467 0.0979 0.0478 0.0615 0.1093

0.0053 0.0005 0.0008 0.0021 0.0014 0.0016 0.0026 0.0050 0.0049 0.0054

0.0466 0.0048 0.0122 0.0397 0.0051 0.0137 0.0415 0.0054 0.0158 0.0457

0.0080 0.0008 0.0020 0.0063 0.0010 0.0023 0.0068 0.0011 0.0031 0.0082

0.8496 0.1977 0.3971 0.7283 0.1851 0.4209 0.7563 0.1284 0.3532 0.7406

0.2336 0.0370 0.0851 0.1828 0.0400 0.0909 0.1956 0.0308 0.0873 0.2000

0.6780 0.7101 0.4108 0.3529 0.9165 0.7341 0.4002 0.9985 0.9851 0.6851

1.0232 1.0808 1.0753 1.0502 0.6330 1.0668 1.0589 0.2127 0.6125 1.0381

0.0767 0.0264 0.0354 0.0695 0.0305 0.0389 0.0713 0.0451 0.0534 0.0830

0.0108 0.0011 0.0029 0.0095 0.0016 0.0032 0.0096 0.0050 0.0057 0.0107

0.0199 0.0020 0.0043 0.0136 0.0025 0.0059 0.0148 0.0027 0.0078 0.0194

0.0125 0.0013 0.0035 0.0111 0.0013 0.0036 0.0117 0.0014 0.0041 0.0122

0.3709 0.0844 0.1425 0.2562 0.0919 0.1818 0.2790 0.0645 0.1748 0.3214

0.2525 0.0538 0.1154 0.2115 0.0484 0.1141 0.2244 0.0355 0.0983 0.2144

1.3943 1.4923 1.5309 1.5769 1.0620 1.4800 1.5044 1.0022 1.1320 1.3581

1.6082 1.7438 1.8490 1.8580 0.8435 1.6617 1.8249 0.2831 0.8270 1.5594

0.0366 0.0037 0.0109 0.0368 0.0037 0.0108 0.0366 0.0036 0.0110 0.0367

0.0070 0.0007 0.0020 0.0068 0.0007 0.0020 0.0068 0.0007 0.0021 0.0068

25 25 25 25 25 25 25 25 25 25

72 73 74 75 76 77 78 79 80 81

18 18