HDTenEightyP/NetNews huggingface dataset:
Organization: Arizona State University
Date: Saturday, 9 Jan 1993 13:56:00 MST
From: <ATG2G@ASUACAD.BITNET>
Newsgroups: bit.listserv.stat-l
Subject: Re: Roundoff of various formulae in spreadsheets

As a matter of curiosity (since I don't deal in ppm scales) and to
extend the "platform" question, I tried to replicate the STDEV results
on an SE running Excel 4.0, no FPU.  I found discrepancies beginning
roughly at the point that the interquartile range falls below
one 10-millionth of the mean.  Apparently the precision has tightened
up a bit (no pun intended, but there it is) vis-a-vis 3.0, but the
formula is as before.

There is a LINEST function in 4.0 that returns multiple regression
statistics very fast and very accurately for most data, but I was
able to make it return an error value using data that other Excel 4.0
functions (determinant, matrix mult, etc.) are able to handle.

Unrepentant, I continue to trust Excel, for statistical purposes,
neither more nor less than anything else that comes shrink-wrapped.

(Flame deflectors on.)

Conrad Carlberg

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Date:         Tue, 5 Jan 1993 15:54:00 EST
From:         dxa6@CCDOSH1.EM.CDC.GOV
Subject:      Re: Spreadsheet Software

Thanks to everyone who has responded to my additional posting on this
subject, and who has further clarified the issue of computational analysis
and numerical precision.  I did not mean to impugn Phil Miller.  Although I
am certain that someone used the word "wrong" in the context that I claimed
they did, I'm not at all sure who it was.

At any rate, I find this entire business to be quite fascinating.  I was
aware of the need for different computational algorithms under certain
circumstances, but I think I will look into it some more now.  Perhaps I'll
start by researching whether there are differences in how my trusty old HP 67
pocket calculator handled numbers versus the Compaq Deskpro 50M (486DX2
processor and 387-compatible coprocessor) that I have on my desk now.

--Dave
_____________________________________________________________________________
David R. Arday, M.D., M.P.H.
Office on Smoking and Health
Centers for Disease Control
dxa6@ccdosh1.cdc.em.gov
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Date:         Thu, 7 Jan 1993 11:05:00 EST
From:         dkw4@NIOSHE2.EM.CDC.GOV
Subject:      Summary of discussion available

STAT-Lers,

Since I found it so interesting, I made a summary for my co-workers of all
the STAT-L (and in-NIOSH-house) discussion on using spreadsheets to perform
statistical analyses.

If any of you would like a copy, please send me your e-mail address.

Thanks to all of you who contributed - your help is invaluable.

Deanna

*-----------------------------------------------------------------*
Deanna Wild
Statistician
National Institute for Occupational Safety and Health
4676 Columbia Parkway  MS: R-4
Cincinnati, Ohio  45226

INTERNET: DKW4@NIOSHE2.EM.CDC.GOV
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Date:         Wed, 6 Jan 1993 09:20:00 EST
From:         "SI00::SIGNORINOC" <SIGNORINOC%SI00.decnet@V9.HANSCOM.AF.MIL>
Subject:      Re: calculators and computers: precision

                          E L E C T R O N I C   M A I L
                     (DDN Host Address:  V3.HANSCOM.AF.MIL)

                                        Date:      06-Jan-1993 09:19
                                        From:      Lt Curtis S. Signorino
                                        Username:  SIGNORINOC
                                        Dept:      ESC/XRPM
                                        Tel No:    617-377-7483 (DSN 478)

TO:  _WINS%                               ( _DDN[STAT-L@VM1.MCGILL.CA] )


Subject: Re: calculators and computers: precision




 -----------------------------A T T A C H M E N T------------------------

                          E L E C T R O N I C   M A I L
                     (DDN Host Address:  V3.HANSCOM.AF.MIL)

                                        Date:     06-Jan-1993 09:17
                                        From:     Lt Curtis S. Signorino
                                                  SIGNORINOC
                                        Dept:     ESC/XRPM
                                        Tel No:   617-377-7483 (DSN 478)

TO:  VMSMail User WINS%"<DANIEL%UHU       (
 WINS%"<DANIEL%UHUNIX.BITNET@VM1.MCGILL.CA>"@SI09@MRGATE )


Subject: Re: calculators and computers: precision

    Someone brought up the difficulty of computing large factorials.
    Many times the need to compute large factorials or large gamma
    function values is for an expression containing a ratio of
    factorials or gamma function values.  While the individual
    factorials or gamma function values will cause an overflow, the
    resulting ratio is quite manageable.  The trick, then, is to
    compute the ratio without having to compute the original numerator
    or denominator.  Using the relationships

         X = exp( ln(X) )

    and

         ln(X1/X2) = ln(X1) - ln(X2),

    the factorial and gamma ratios can be computed as

         X1!
         -- = exp( lnfact(X1) - lnfact(X2) )
         X2!

    and

         Gamma(X1)
         --------- = exp( lngamma(X1) - lngamma(X2) )
         Gamma(X2)

    where lnfact() and lngamma() are numerical methods-based
    functions (using something like Sterling's formula for lngamma[]).
    These functions can be found in a number of numerical methods
    books.  I believe _Numerical_Recipes_ has both.

         I've found the precision of the above methods to be
    acceptable for my research.  For those who are familiar with the
    above, have you had any problems with poor precision due to the
    numerical methods?

    curt signorino
    signorinoc@v3.hanscom.af.mil
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Date:         Thu, 7 Jan 1993 13:59:03 -0500
From:         712_dbh3@WHITE.WHOI.EDU
Subject:      STRATIFIED SAMPLING DESIGNS

At the Northeast Fisheries Science Center, we conduct two sampling surveys
of fish abundance using bottom trawl nets using a stratified random sampling
design.  As is often the case we would like to improve the precision
of estimates from our survey and their robustness without having to take
more samples. I would appreciate any information on references in the
statistical literature pertaining to a couple of questions.

1.  Has any recent work been done on restricted randomization schemes?
    Rather than do a stratified sampling design, one alternative is to do
    a systematic (spatially) sampling.  A compromise type of design would
    be to do a stratified design, but restrict the spatial allocation of
    sampling sites within each strata to achieve a more uniform (but not
    systematic) spatial distribution of sampling effort.

2.  Is there such a thing as a stratied median?  One can certainly
    compute the median for each stratum, but how do you combine these
    medians (since averaging the medians would not necessarily give you
    the median for the whole survey area).

Any information on these points would be greatly appreciated.  If there is
sufficient interest and response, I will post a summary of mailings.

Thanks in advance.



Daniel Hayes
National Marine Fisheries Service
Northeast Fisheries Science Center
166 Water Street
Woods Hole, MA 02543-1097
voice  (508) 548-5123 x317
email  712_dbh3@white.whoi.edu
---------------------------------------------------------------------------
Here is Edward Bear, coming downstairs now, bump, bump, bump, on the back
of his head, behind Christopher Robin.  It is, as far as he knows, the only
way of coming downstairs, but sometimes he feels that there really is another
way, if only he could stop bumping for a moment and think of it.  And then
he feels that perhaps there isn't.  Anyhow, here he is at the bottom....

  -- A.A. Milne
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Organization: K.U.Leuven (Belgium)
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Date:         Mon, 4 Jan 1993 16:34:13 UTC+0100
From:         Vuylsteke Magda <LAAAA02@BLEKUL21.BITNET>
Subject:      qualitative variables in principal component analysis.

I concentrate on this topic the last ? years. A good approach is coming
from the University of Leiden in the Netherlands by a group around
De Leeuw. In '89 they published their ideas in "Non Linear Multivariate
Analysis".  Albert Gifi. John Wiley and Sons.
PROC PRINQUAL was inspired by these techniques while W.Kuhfeld worked
together with this group. Is this correct Warren?  I have the impression
that the technique mentioned by some of the list - I lost the name - can
be compared with the MORALS approach by Jan De Leeuw. But more details
would be necessary for an exact comparison.  Thomson's remark concerning
correspondence analysis is correct if all the variables are nominal and
then transformed to dummy variables.

Drs. Magda Vuylsteke              Telephone (32)-16-286611 ext2215
Computing Center                  Fax       (32)-16-207168
Center of Statistics
University of Leuven
de Croylaan, 52a
3001 Heverlee                     E-mail:laaaa02@blekul21
Belgium
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Date:         Tue, 12 Jan 1993 08:32:27 -0500
From:         JAIS@FRSIM51.BITNET
Subject:      unsubscribe

Please unsubscribe me from STAT-L. I will losing my access in the near future
JP JAIS
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Date:         Mon, 4 Jan 1993 10:30:28 EST
From:         Stephen Salbod <SALBOD1@PACEVM.BITNET>
Subject:      Path coefficients

DEAR statlers,
     I HAVE EIGHT PERSONALITY MEASURES (TAKEN FROM THE MILLON ADOLESCENT
PERSONALITY INVENTORY) AND WOULD LIKE TO COMPUTE CORRELATIONS BETWEEN
THEM. THE PROBLEM 1) IS THAT ANY PAIR WILL SHARE ITEMS 2) SCALES
ARE OF DIFFERENT LENGTHS AND 3) SHARED ITEMS IN SOME PAIRED SCALES
WILL NOT BE SCORED IN THE SAME DIRECTION.
     I AM NEED TO COMPUTE COEFFICIENTS BETWEEN SCALES FOR A PATH MODEL
AND BECAUSE OF THE OVERLAP CANNOT SIMPLY PUT 0S. HAS ANYONE RECOMMENDATI
OR STILL BETTER YET, DOES ANYONE KNOW OF A GOOD REFERENCE.

     THANK YOU IN ADVANCE FOR ANY HELP.

PRODUCED AND DIRECTED BY STEPHEN SALBOD (SALBOD1@PACEVM)
        ON LOCATION AT PACE UNIVERSITY, NY
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Date:         Tue, 5 Jan 1993 18:03:50 GMT
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From:         "Randall D. Tobias" <sasrdt@UNX.SAS.COM>
Subject:      Re: Matrix problem

I'm posting this solution rather than just mailing, in order to
advertise my primary source.

In article <STAT-L%93010511153853@VM1.MCGILL.CA>, Just Jensen
<LOFJUST@VM.UNI-C.DK> writes:
|> During this procedure I have to prove a matrix identity that I think is
|> well known but i do'nt seem to be able to prove it.
|>
|> Let A be a symetric P.d. matrix.
|>
|> Partition A as A = ! A11 A12 !
|>                    ! A21 A22 !
|>
|> Let C=Inv(A)= ! C11 C12 !
|>               ! c21 C22 !
|>
|> where C is partitioned in the same way as A and inv means inverse.
|>
|> Then the following relationship exists:
|>
|> Inv(A11)*A12 = -C12*Inv(C22)
|>
|> what I need is the proof! (any hints?? or better full proofs)

I just happen to be looking at the same sort of partitioned inverses
right now myself, in connection with block designs.  The appendices in
Mardia, Kent, and Bibby (_Multivariate_Analysis_, Academic Press, 1979)
are my standard reference for all sorts of useful matrix identities
like this.  Formula (A.2.4g) there gives

   C12 = -Inv(A11 - A12*Inv(A22)*A21)*A12*Inv(A22)
   C22 =  Inv(A22 - A21*Inv(A11)*A12)

Thus,

   -C12*Inv(C22) =   Inv(A11 - A12*Inv(A22)*A21)
                   * A12*Inv(A22)*(A22 - A21*Inv(A11)*A12)
                 =   Inv(A11 - A12*Inv(A22)*A21)
                   * (A12 - A12*Inv(A22)*A21*Inv(A11)*A12)
                 =   Inv(A11 - A12*Inv(A22)*A21)
                   * (A11 - A12*Inv(A22)*A21)*Inv(A11)*A12
                 = Inv(A11)*A12

as required.

Question: Is non-singularity of all the relevent matrices really
          required?  I doubt it.

|> Thanks in advance.

Glad to help!
--

Randy Tobias          SAS Institute Inc.     sasrdt@unx.sas.com
(919) 677-8000 x7933  SAS Campus Dr.         72450.2545@compuserve.com
(919) 677-8123 (Fax)  Cary, NC   27512-8000  norat@aol.com

 ... just my $(-exp(2*sqrt(-1)*arcos(0))/(((2**(2 + 1)) - 1)**2 + 1)).
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Newsgroups: bit.listserv.stat-l
Date:         Mon, 4 Jan 1993 10:37:24 EST
From:         HFJ2000 <HFJ2%RUSHVM.bitnet@UICVM.UIC.EDU>

//DANTAN  JOB
DATABASE SEARCH DD=RULES
//RULES DD *
SEARCH LOG NORMAL IN STAT-L
*PRINT 771 800 1251 1293 1564 1850
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Date:         Thu, 7 Jan 1993 20:10:16 EST
From:         James Arbuckle <V5113E@TEMPLEVM.BITNET>
Subject:      AMOS DRAW now available via ftp

Amos Draw is now available via anonymous ftp from cronkite.temple.edu in
the directory /pub/bin/win. There are two files: amosdpak.exe is a self
extracting archive. amosdpak.txt contains installation instructions.

I have some printed samples of path diagrams drawn by Amos Draw that I
will send on request. I can also mail out copies of Amos Draw on
diskette, but would prefer to do this only as a last resort.

Amos Draw is a Windows program for drawing path diagrams.

James Arbuckle                             Bitnet: v5113e @ templevm
Psychology Department                      Phone: 215-787-1572
Temple University                          Fax: 215-643-5596
Philadelphia, PA  19122
USA
From: nichols@spss.com (David Nichols)
Newsgroups: bit.listserv.stat-l
Subject: Re: 2 x 3 contingency table
Date: 6 Jan 93 19:11:29 GMT
Organization: SPSS Inc.

Another way to look at the problem of figuring out where a significant
chi-square statistic comes from is to examine residuals, or more
specifically, standardized and adjusted residuals. The standardized
residuals give a picture of the contribution of the misfit of observed
vs. expected in each cell of the table, and the adjusted residuals are
asymptotically normally distributed and can thus in large samples be
used to test for cells that are mispredicted under the independence
model. See pp. 224-on in Agresti's _Categorical Data Analysis_ for more
information, or some of Haberman's stuff. These residuals are provided
in SPSS in CROSSTABS.

--
 David Nichols        Senior Statistical Support Specialist         SPSS, Inc.
 Phone: (312) 329-3684     Internet:  nichols@spss.com     Fax: (312) 329-3657
*******************************************************************************
 Any correlation between my views and those of SPSS is strictly due to chance.
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Date:         Mon, 4 Jan 1993 17:33:28 GMT
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From:         "Warren F. Kuhfeld" <saswfk@UNX.SAS.COM>
Subject:      Re: qualitative variables in principal component analysis.

In article <STAT-L%93010410353883@VM1.MCGILL.CA>, Vuylsteke Magda
<LAAAA02%BLEKUL21.BITNET@VM1.MCGILL.CA> writes:
|> PROC PRINQUAL was inspired by these techniques while W.Kuhfeld worked
|> together with this group. Is this correct Warren?  I have the impression
|> that the technique mentioned by some of the list - I lost the name - can
|> be compared with the MORALS approach by Jan De Leeuw.

I actually wrote PRINQUAL before I visited Leiden, but it definitely
was inspired by Jan de Leeuw's work, the Gifi book, and all of the
related work that came out of Leiden and UNC.  The PRINQUAL MTV
(maximum total variance) algorithm is like the Gifi PRINCALS algorithm.
PRINQUAL also has an MGV (minimum generalized variance) algorithm, which
iteratively regresses each variable on all of the others.  MORALS, for
multiple optimal regression using alternating least squares, is
implemented in PROC TRANSREG, as is CANALS (canonical correlation with
alternating least squares).
--
----------------------------------------------------------------------
Warren F. Kuhfeld          Statistical R & D      (919) 677-8000 x7922
saswfk@unx.sas.com         SAS Institute Inc.     (919) 677-8123 (Fax)
                           Cary, NC 27513-2414
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Newsgroups: bit.listserv.stat-l
Date:         Fri, 8 Jan 1993 09:28:22 -0600
From:         wiorkow@UTDALLAS.EDU

     The reason that statisticians are often not put on TV shows or even panels
 is that we have this nasty habit of being faithful to our profession and to th
e truth.  About six years ago I was on a panel of the National Academic of Scie
nces studying the effect of highway speed limitations on mortality and accident
rates.  I was the only statistician (although a well trained economist also was
 on the panel), the rest of the folks were ones with a vested interest in the a
rea including representatives of state highway departments, and many people who
 had written on the relationship.  We reviewed many studies, none of which show
ed any relationship of accident or death rates with average speed.  What did sh
ow up was a relationship between the rates and the variability in speeds.  In o
ther words if everyone went 85 mph on the interstates there would be fewer acci
dents than if some went 55 and others went 65.  The two of us were unsuccessful
in convincing the other 15 or so members on emphasizing this point.  (Science o
n panels is done by majority).  I would be most interested in seeing the data o
n which the "secondary smoke" report is based.  This is just the kind of issue
that the ASA should review to see if in fact the "unbiased" researchers are at
least doing the statistical inference correctly.  I was particularly intrigued
by the statment to wit that several of the studies did not show significance si
nce they were too small.  We all know that the underlying theory of statistical
inference indicates that any difference, no matter how small in effect, will be
 detected if the sample sizes are large enough.  The real question has to do wi
th what the probabilities of contracting disease are.  I also noted that this w
as never stated.  Instead we got figures on number of deaths (3000 as I recall)
out of a population of 300,000,000 gives a probability in a single year of abou
t 1 in 1000.  This strikes me as sufficiently small to not burden out society w
ith the costs of administering and policing this issue when those same funds co
uld be used to help people in slums exposed to much greater risk factors.  But
of course that is a much harder problem.

                                          John J. Wiorkowski
                                          Professor of Statistics
                                          University of Texas at Dallas
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Date:         Thu, 7 Jan 1993 09:28:17 WET
From:         "R.A.Reese" <R.A.Reese@SEQ.HULL.AC.UK>
Subject:      Disclaimers.

Just a random thought but why do so many contributors end their messages with a
disclaimer?  Is it their company requirement or are they just being cute? I
 think
we should be told.
--
(R.) Allan Reese        Janet:          r.a.reese@uk.ac.hull
Head of Applications    Direct voice:   +44 482 465296
Computer Centre         Voice messages: +44 482 465685
Hull University         Fax:            +44 482 466441
Hull HU6 7RX, U.K.
--------------------------------------------------------------------------------
Disclaimer: any thoughts I put out are, unless otherwise attributed or unless I
forgot the source or intended to plagiarize, the product of my own fertile and
disreputable mind.  On the other hand, anyone who disagrees with me is
 misguided,
malevolent, depraved or just plain daft. (e & o e)
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Date:         Wed, 6 Jan 1993 00:37:55 -0500
From:         John Wendell <WENDELL@UHCCVX.UHCC.HAWAII.EDU>
Subject:      Textbook formulas and computers

Well, since the spreadsheet question has resurfaced, I'll show my
ignorance and shoot this question to the list.  I had great fun over
the summer learning Maple and have been using it to calculate
statisistics based on textbook and journal formulas (you know, alot of
stuff in the journals isn't available on SAS etc., particularly the
Bayesian stuff), but I'm always careful to use it in it's "exact" mode
(I avoid decimal points in my data, ie. I put in 1/100 instead of
.001).  From what my limited knowlege of how the program actually
works, I think I cann't possibly have any floating point type errors
in this mode (although it can take a lot of time to run and likes to
eat disk space in this mode.)  Once the calculations are done I'm
often left with a huge and bizzare fraction or polynomial to which I
apply evalf(",10) to reduce it to decimal form.  Am I really avoiding
computational pitfalls by doing it this way or am I just fooling
myself.

Aloha, - John  WENDELL@UHCCVX.UHCC.HAWAII.EDU.internet (Or just
WENDELL@UHCCVX.bitnet)
-------
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From: dmurdoch@mast.queensu.ca (Duncan Murdoch)
Subject: Re: calculators and computers: precision
Organization: Queen's University
Date: Wed, 6 Jan 1993 15:11:38 GMT

In article <STAT-L%93010605170684@VM1.MCGILL.CA> Ronan M Conroy <RCONROY@IRLEARN.UCD.IE> writes:
>Phil Miller mentioned 69! as the
>biggest factorial that the PC will handle. This, by less than
>a coincidence, is the limit of what my Sharp EL-506H and my Tandy
>(submerged on the desk, no doubt, at the moment) will handle.
>69!/68! is correctly evaluated by them both as being 69. 

In fact "the biggest factorial a PC will handle" is not a well-defined 
number.  PC's don't have a single floating point representation; each 
representation has different limits.  If you have a numeric coprocessor, the 
single, double and temp real types (4, 8 and 10 bytes resp.) are supported 
by hardware; they can calculate factorials up to 34!, 170!, and 1754!.  
However, there are lots of packages providing arithmetic up to much higher 
limits in software.

Duncan Murdoch
dmurdoch@mast.queensu.ca
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