bluuebunny/crossref_metadata_2025 huggingface dataset:
EXAMPLES OF MINIMUM VARIANCE ESTIMATION1
Authors: Bartlett M. S.
Published: February 2008

In this sequel to a previous discussion of minimum variance estimation (Bartlett, 1982), the gain with conditional estimation procedures is illustrated for the location parameter for (i) the rectangular distribution; (ii) a triangular distribution (typifying an asymmetric case). This note concludes with further remarks on the multi‐sample and multi‐parameter cases.
MULTIPLE COMPARISONS AND SELECTION1
Authors: Bofinger Eve
Published: February 2008

The selection of the “best” of k populations and subsequent prediction for this population versus “the rest” is compared with the Newman‐Keuls multiple comparison procedure for “separating” populations.
MINIMUM SIGNIFICANCE AND DISTRIBUTION FREE TESTS1
Authors: Brown B. M.
Published: February 2008

A general way of testing in the presence of nuisance parameters is to choose from a family of tests the one to maximize evidence against null hypothesis; that is, to minimize the significance level. This method yields exact tests when applied to distribution‐free testing in various statistical designs; arbitrary choice of score functions is eliminated. However, the exact null distributions are highly non‐normal, and there are problems with both computation and asymptotic theory.
ON THE REDUCTION OF BIAS IN DENSITY ESTIMATES1
Authors: Hall Peter
Published: February 2008

We propose a method for simultaneously estimating a density function and its derivatives based on a recursive reduction of bias in the usual one‐step estimator—in effect, a jackknife. The procedure is computationally simple and requires only the inversion of a triangular matrix with easily‐calculated elements.
THE CONVERGENCE OF AUTOCORRELATIONS AND AUTOREGRESSIONS1
Authors: Hannan E. J. , Kavalieris L.
Published: February 2008

For a general class of scalar stationary processes, essentially those for which the best linear predictor is the best predictor (in the mean square sense), it is shown that, under fairly minor additional conditions, the sample autocorrelations converge to the true values almost surely and hniformly in the lag, t, at a rate (T‐1log T)1/2, where T is the sample size. For ARMA processes, if |t|(log T)a, a < ∞, the rate is the best possible, namely (T‐1log log T)1/2. In particular the somewhat implausible condition, on the innovations, that E{ε(t)2| Ft‐l} is constant is avoided in these results. The theorems are used to discuss autoregressive approximation. When the stationary process is a vector process the condition on the innovation sequence, ε(t), that E{ε(t)ε(t)| Ft‐l} be constant, cannot be entirely avoided in relation to autoregressive approximation. This is also discussed.
SOME PROPERTIES OF A RANDOM LINEAR DIFFERENCE EQUATION1
Authors: Pakes Anthony G.
Published: February 2008

Some simple conditions are given for the absolute continuity of the limiting distribution of a random linear difference equation. These results are applied to the super‐critical Bellman‐Harris branching process with immigration. When the coefficients of the difference equation are non‐negative and there is no limiting distribution, it is shown that the asymptotic behaviour of the solutions is the same as that of the partial sums of a divergent random power series. A number of limit theorems are given for the latter situation.
AN EXAMINATION OF THE EIGENVECTOR CONDITION IN THE DURBIN‐WATSON TEST
Authors: Cassing Shirley A. , White Kenneth J.
Published: February 2008

This paper examines the power of the Durbin‐Watson test for autocorrelation when the eigenvector condition for a uniformly most powerful (UMP) test may not be satisfied.
ASYMPTOTIC TESTS FOR THE CONTINUOUS TIME MARKOV BRANCHING PROCESS WITH IMMIGRATION
Authors: Hudson Irene L.
Published: February 2008

This paper presents limit distributions for the modified score and the likelihood‐ratio (LR) statistic for testing a composite hypothesis involving the split intensity and mean of the offspring distribution of the supercritical continuous time Markov branching process allowing immigration (CBPI). The immigration intensity and mean are treated as nuisance parameters.
ON THE NONCENTRAL DISTRIBUTION OF A RANDOM MATRIX USEFUL IN CLASSIFICATION THEORY
Authors: Rogers G. S. , Kabe D. G.
Published: February 2008

To prove the optimality properties of the maximum likelihood (and also minimum distance) discriminant rule Rogers (1980, p. 98) embeds the maximum likelihood discriminant function in a Cauchy‐Schwartz inequality. This embedding procedure of Rogers (1980) may be used to derive a new distribution for Anderson's (1958) classification statistic.
NOTES ON CONFIDENCE REGIONS FOR A LINEAR MODEL
Authors: Beth M.
Published: February 2008

Several confidence regions for the means and standard deviation of a linear model are noted. Simulation to find the appropriate percentage points of sampling distributions is suggested as a practical way of constructing rectangular shaped regions.
A NORMAL APPROXIMATION TO THE FISHER DISTRIBUTION
Authors: Clark R. M. , Morrison B. J.
Published: February 2008

A simple normal approximation is given for the joint probability density function of the polar co‐ordinates (θ, ψ) of a random vector following the Fisher distribution with arbitrary mean direction (θ0, ψ0). The approximation leads to simple inference procedures which are particularly useful in regression models. Conditions for the adequacy of the approximation are investigated and summarized in tabular form.
AN ANALYTIC FORM FOR THE CUMULATIVE DISTRIBUTION FUNCTION OF THE BELL‐DOKSUM STATISTIC
Authors: Clarke A. P. , Marwood W.
Published: February 2008

A closed form analytic expression for the Bell‐Doksum Statistic is developed. The use of the generalized hypergeometric function to evaluate the expression is demonstrated, and a table of critical values for 2 n 25 is presented.
ASYMPTOTIC DEFICIENCY OF THE JACKKNIFE ESTIMATOR
Authors: Akahira Masafumi
Published: February 2008

In this paper it is shown that the bias‐adjusted maximum likelihood estimator (MLE) is asymptotically equivalent to the jackknife estimator in the variance up to the order n‐1 and the asymptotic deficiency of the jackknife estimator relative to the bias‐adjusted MLE is equal to zero.
ON CHARACTERIZING SOME BIVARIATE DISCRETE DISTRIBUTIONS
Authors: Papageorgiou H.
Published: February 2008

The bivariate (correlated) Poisson, binomial, negative binomial and logarithmic distributions are characterized by the conditional distribution of one random vector on the other and a regression function of the second random vector on the first. Characterizations of the above distributions when their component random variables are independent are also included.
ON A TEST OF FIT IN TIME SERIES MODELS
Authors: Beveridge Stephen
Published: February 2008

It is shown that a test for adequacy of a fitted Arma (p, 4) model based on forecast errors, has the same asymptotic expected value whether the null hypothesis is true or false. A sampling study supports the conclusion in small to moderately large samples and indicates that for sample sizes commonly used by practitioners, the power of the test is very low.
IMPROVING UPON THE BEST INVARIANT ESTIMATOR IN MULTIVARIATE LOCATION PROBLEMS
Authors: Puri Madan L. , Ralescu Dan A.
Published: February 2008

We are concerned with estimators which improve upon the best invariant estimator, in estimating a location parameter θ. If the loss function is L(θ ‐ a) with L convex, we give sufficient conditions for the inadmissibility of δ0(X) = X. If the loss is a weighted sum of squared errors, we find various classes of estimators δ which are better than δ0. In general, δ is the convolution of δ1 (an estimator which improves upon δ0 outside of a compact set) with a suitable probability density in Rp. The critical dimension of inadmissibility depends on the estimator δ1 We also give several examples of estimators δ obtained in this way and state some open problems.
RISK ANALYSIS IN MORE THAN ONE DIMENSION
Authors: Hasofer A. M. , Veneziano D. , Banon H.
Published: February 2008

summary

The concept of risk function is extended to the situation where the “life” of the specimen is represented by a vector of dimension greater than one. Model‐building, estimation of parameters and goodness of fit are discussed.

The model is applied to fatigue failure of reinforced concrete beams where two separate indicators of damage are monitored.
LINEAR MINIMAX ESTIMATORS FOR ESTIMATING A FUNCTION OF THE PARAMETER
Authors: Puri Madan L. , Ralescu Dan A. , Ralescu Stefan S.
Published: February 2008

summary

In this note we provide sufficient conditions for the minimaxity of linear estimators of the form aX+b in the one‐parameter exponential family for estimating a differentiable function g(θ) with normalized quadratic loss. We provide some examples which show that the natural estimator X is minimax in estimating a function of the parameter (different from the mean).
THE GEOMETRY OF SPECIFICATION ERROR
Authors: Fisher Gordon , McAleer Michael
Published: February 2008

summary

This paper discusses the traditional specification problem from a geometric (or co‐ordinate‐free) viewpoint. While the traditional emphasis is on the properties of estimators, the geometric approach also allows an easy development of corresponding results for inference. Errors arising from artificial inclusion or exclusion of variables are considered in terms of augmentations or restrictions on a given maintained hypothesis, and this allows a corresponding interpretation of tests based upon the Wald and Lagrange Multiplier Principles. It is demonstrated that biases arising from incorrect exclusion of variables do not invalidate the traditionalF‐test.
BALANCED ARRAYS AND WEIGHING DESIGNS
Authors: Saha G. M. , KAGEYAMA SANPEI
Published: February 2008

Dey (19711, Saha (1975), Kageyama & Saha (1983) and others have shown how optimum chemical balance weighing designs can be constructed from the incidence matrices of balanced incomplete block (BIB) designs. In this paper, it is shown that weighing designs can be constructed from some suitably chosen two‐symbol balanced arrays of strength two, which need not always be incidence matrices of BIB designs. The findings lead us to construct new optimum chemical balance weighing designs from incidence matrices of BIB designs.
THE KOMLÓS‐MAJOR‐TUSNÁDY APPROXIMATIONS AND THEIR APPLICATIONS
Authors: CSÖRGÖ SÁNDOR , Hall Peter
Published: February 2008

Any order‐invariant function of a sequence of sample values may be expressed as a functional of the sample's empiric distribution function. This suggests that a very general approach to the theory of functions of sample values can be based on the empiric distribution function. The Komlós‐Major‐Tusnhdy (KMT) approximation provides a remarkable, mathematically tractable representation for the empiric distribution function of a random sample. Our aim in this paper is to describe the KMT approximation, particularly as it relates to other forms of approximation, and to survey some of its many applications.
ESTIMATING POPULATION SIZE FROM CAPTURE‐RECAPTURE EXPERIMENTS IN CONTINUOUS TIME
Authors: Becker Niels G.
Published: February 2008

Estimates for the size of a closed population are given for multiple recapture studies in continuous time. The estimates are derived by a method of moments for martingales. An estimate and associated standard error of the population size are derived for a homogeneous population when the capture rates are permitted to depend on time in an unspecified manner. Corresponding results are obtained when the capture rates vary among individuals as well. Explicit expressions are given for these estimates and standard errors which involve only simple computation.
A TEST FOR THE NONPARAMETRIC TWO SAMPLE SCALE PROBLEM
Authors: Deshpandé Jayant V. , Kusum Kalpana
Published: February 2008

We propose a distribution‐free test for the nonparametric two sample scale problem. Unlike the other tests for this problem, we do not assume that the two distribution functions have a common median. We assume that they have a common quantile of order a (not necessarily 1/2). The test statistic is a modification of the Sukhatme statistic for the scale problem and the Wilcoxon‐Mann‐Whitney statistic for stochastic dominance. It is shown that the new test is uniformly more efficient (in the Pitman sense) than the Sukhatme test and has very good efficiency when compared to the Mood test.
ASYMPTOTIC DISTRIBUTIONS OF MATCHED‐PARIS PERMUTATIO STATISTICS BASED ON DISTANCE MEASURES
Authors: Brockwell Peter J. , Mielke Paul W.
Published: February 2008

A technique for deriving asymptotic distributions of matched‐pairs permutation statistics based on distance measures is discussed and applied to four specific examples recently considered by Mielke & Berry (1982).
REGIONAL ECONOMIC‐DEMOGRAPHIC MODELLING AND PROJECTION: REVIEW OF AN INTERNATIONAL CONFERENCE
Authors: Williams Pamela
Published: February 2008

The state‐of‐the‐art in economic‐demographic modelling of regional populations was presented at the International Conference on Forecasting Regional Population Change and its Economic Determinants and Consequences held at Airlie House, Virginia, U.S.A. over May 26 to 29, 1982. This review of papers presented at the Conference concludes that such modelling is at an early stage of development and currently provides only an adjunct to more conventional methods of regional forecasting. Given expected future improvements in the theory, data and techniques of economic‐demographic modelling, such models could soon provide a worthwhile alternative.
THE INFINITELY DEEP DAM WITH SEASONAL MARKOV INFLOWS—A SIMPLIGYING MODIFICATION
Authors: Phatarfod Ravindra M.
Published: February 2008

This is an extension of the work reported in Phatarfod (1981). Here we make the further assumption that the inputs to a bottomless dam are independent from year to year, although they are dependent within a year. It is shown that this assumption drastically simplifies, computationally and analytically, the limiting distribution of the depletions.
EXISTENCE OF A SEN—YATES—GRUNDY FORM FOR A DISPERSION
Authors: Liu Tzen‐Ping
Published: February 2008

The condition of fixed sample size is essential for the existence of a Sen‐Yates‐Grundy form variance and its design unbiased estimator, in the problem of estimating the mean, variance and covariance of a finite population.
DENSITY FUNCTION APPROXIMATION WITH PARTICULAR REFERENCE TO THE DISTRIBUTION OF OVERLAP OF CIRCLES
Authors: Jarreit R. G. , Liow S. , Morgan B. J. T.
Published: February 2008

summary

Given that two circles overlap, the area in common is a function of the distance between their centres. This paper adopts a suitable random distribution for the intercentre distance and then derives the distribution of the area of overlap. An approximation is sought for the density function using a criterion which enables bounds to be placed on the difference between the moments of the density function and those of the approximation. This is an approach of general applicability. The importance of matching the end‐point behaviour of the density and the approximation is stressed. It is shown that the distribution of the area of overlap may be well approximated by a mixture of beta distributions in which the parameters change smoothly with the ratio of radii.
DATA‐BASED CHOICE OF THE SMOOTHING PARAMETER FOR A KERNEL DENSITY ESTIMATOR
Authors: Hart Jeffrey D.
Published: February 2008

summary

The problem of optimally choosing the smoothing parameter of a Fourier integral density estimator (FIE) is addressed. A new data‐based method of so doing is shown to be related to, but an improvement over, the method of Davis (1981). It is shown that Davis' method does not lead to consistent estimation of certain, principally multimodal, densities. In a simulation study involving the bimodal mixture of two normal densities, the new method is seen to represent a substantial improvement.
A COMPARISON OF TESTS OF UNIFORMITY FOR SPHERICAL DATA
Authors: Diggle P. J. , Fisher N. I. , Lee A. J.
Published: February 2008

summary

A comparison is made af three tests of uniformity for spherical vector data, and of the corresponding tests of uniformity for spherical axial data.
CALCULATION OF MULTIVARIATE NORMAL PROBABILITIES—ANOTHER SPECIAL CASE
Authors: Moran P. A. P.
Published: February 2008

summary

The problem of calculating orthant probabilities for sets of variables (X1,., Xn) is considered in the case where they are jointly normally distributed with zero means and a correlation matrix such that the correlation between Xi and Xi is zero if |i‐j|> 1. An effective method is given which works for quite large n when the correlations between Xi and Xi+1 have the values 1/2, 2/5, 3/10, 4/17, 5/26,. and more approximate methods are given for other values. The accuracy is investigated numerically.
CRITICAL VALUE APPROXIMATIONS FOR TESTS OF LINEAR REGRESSION DISTURBANCES
Authors: Evans Merran A. , King Maxwell L.
Published: February 2008

summary

Two important classes of tests for non‐spherical disturbances in the linear regression model involve test statistics whose null distributions and hence critical values depend on the regressors. This paper investigates the accuracy of the normal, two moment beta and four moment beta approximations to the critical values of such tests. An empirical experiment aimed at evaluating the accuracy of the approximations for a variety of tests against autocorrelation and heteroscedasticity is conducted. Overall the approximations are found to provide reasonably accurate critical values with skewness being a factor determining the degree of accuracy.
SAMPLE SURVEYS VERSUS EXPERIMENTS, CONTROLLED OBSERVATIONS, CENSUSES, REGISTERS, AND LOCAL STUDIES12
Authors: Kish Leslie
Published: February 2008

Can we find some common principle in the three comparisons? Lacking adequate time for a thorough exploration, let me suggest that representation is that common principle. I suggested (section 4) that judgment selection of spatial versus temporal extensions distinguish “longitudinal” local studies from “cross‐section” population sampling.

We had noted (section 3) that censuses are taken for detailed representation of the spatial dimension but they depend on judgmental selection of the temporal. Survey sampling lacks spatial detail but is spatially representative with randomization, and it can be made timely. Periodic samples can be designed that are representative of temporal extension. Furthermore, spatial and temporal detail can be obtained either through estimation or through cumulated samples [Purcell and Kish 1979, 1980; Kish 1979b, 1981, 1986 6.6]. Registers and administrative records can have good spatial and temporal representation, but representation may be lacking in population content, and surely in representation of variables.

Representation of variables and of the relations between variables and over the population are the issues in conflict between surveys, experiments, and observations. This is a deep subject, and too deep to be explored again, as it was in section 2.

A final point about limits for randomization to achieve representation through sampling: randomization for selecting samples of variables is beyond me generally, because I cannot conceive of frames for defined populations of variables. Yet we can find attempts at randomized selection of variables: in the selection of items for the consumer price index, also of items for tests of IQ or of achievements. Generally I believe that randomization is the way to achieve representation without complete coverage, and that it can be applied and practised in many dimensions.
DOMAIN ESTIMATION IN FINITE POPULATIONS1
Authors: Chaudhuri Arijtt , Mukeriee Bahul
Published: February 2008

This paper suggests unbiased estimators (UE's) for the size, mean and total of a domain, with specific features, in a given finite population on the basis of simple random sampling without replacement (SRSWOR) continued till a preassigned number of domain members is observed.
DETECTION AND TESTING OF DIFFEFENT TYPES OF OUTLIER IN LINEAR STRAUCTURAL RELATIONASHIPS
Authors: Barnett Vic
Published: February 2008

The linear structural model provides one way of modelling a linear relationship between two random variables. It is well known that problems of unidentifiability arise for unreplicated observations and normal error structure. As in all data sets, outliers can arise and methods are needed for detecting and testing them. An outlier‐generating model of mean–slippage type can be used to characterise four different forms of outlier manifestation. It is interesting to find that the unidentifiability problem provides no obstacle for detecting or testing the outliers for three of the four forms. Detection principles, and specific discordancy tests, are derived and illustrated by application to some data on physical measurements of Pacific squid.
ON VARIANCE ESTIMATION IN UNEQUAL PROBABILITY SAMPLING1
Authors: Kumar Pranesh , Gupta V. K. , Agarwal S. K.
Published: February 2008

The purpose of this article is to propose a model‐based estimator of the variance of the Horvitz‐Thompson estimator. Empirical investigations reveal that the estimator is seldom greatly biased and is quite satisfactory from the stability point of view.
ON EXTERNAL ANCILLARITY1
Authors: Lloyd C. J.
Published: February 2008

summary

Statistics distributed free of a certain parameter (called ancillary for the parameter) are of considerable use when sufficient estimation is not possible (Fisher (1925)). When the model involves, in addition to the parameters of interest, parameters not of direct interest (nuisance parameters) statistics which are distributed free of the latter may be of considerable use also. This requires a study of ancillary statistics which are not functions of the minimal sufficient statistic (MSS). In particular we study the general ancillary given in Williams (1982) and show that it has certain desirable properties including uniqueness under appropriate restrictions. Finally some non‐trivial applications are given.
EXTREME VALUE THEORY FOR CERTAIN NON‐STATIONARY SEQUENCES1
Authors: Feeney G. A. , Sen P. K.
Published: February 2008

Under a Markovian structure on a sequence of random variables which can be partitioned into m(1) jointly dependent subsequences (where within each subsequence the random variables have a common marginal distribution which may vary between the subsequences), the asymptotic distribution theory of the sample extreme values is developed. The asymptotic independence of the subsequence extreme values is also studied.
CHARACTERIZATION OF EFFICIENT SEQUENTIAL SCHEMES FOR POPULATION GROWTH MODELS1
Authors: Manjunath S. M.
Published: February 2008

For population growth models, which include standard processes like Poisson, birth, birth‐death, immigration‐death, simple epidemic andM/M/1queue as particular cases, we obtain efficient sequential schemes and characterize all efficiently estimable functions of the parameters by first deriving a sequential version of the information inequality.
TIMING OF SURVEYS FOR PUBLIC POLICY
Authors: Kish Leslie
Published: February 2008

This keynote address at the 7th Australian Statistical Conference (1984) discusses briefly seven modifications of sample design for improving the usefulness and timeliness of surveys relevant to public poky. These are: better estimates for small domains, cumulating rolling samples, more panel surveys, multipurpose designs for periodic samples, split panel designs (SPD) combining panels with nonoverlapping samples, and frequent collections cumulated for less frequent reporting periods.
EXACT DISTRIBUTION OF CERTAIN GENERAL TEST STATISTICS IN MULTIVARIATE ANALYSIS
Authors: Tang J. , Gupta A. K.
Published: February 2008

In this paper, exact solution of Wilks' type‐B integral equation has been obtained in its most general form as a series of weighted gamma distributions. This general result then gives the distributions of many test statistics in multivariate analysis. In particular the distributions of Wilks' Λ, the sphericity test criterion, and Bartlett's test statistic, are derived in easily computable form.
INDEPENDENT COMPONENT NONPARAMENTRIC ESTIMATION
Authors: Breth M.
Published: February 2008

A unified approach to independent component nonparametric estimation is developed from exchangeable probability coverages. Exact and limit distributions are given.
NEIGHBOUR ANALYSIS OF UNIFORMITY DATA
Authors: Williams E. R.
Published: February 2008

The neighbour model of Williams (1986) is studied using barley uniformity data. Particular attention is paid to the validity of the model. This is done by comparing the variety and residual mean squares in the intra‐Nanalysis.
A MOMENT IDENTITY
Authors: Jones M.C.
Published: February 2008

A moment identity based on the concept of weighted distributions is presented. The identity has potential applications to problems involving the manipulation of expectations of functions of random variables. Several examples, mainly concerning the evaluation of the risk of shrinkage estimators of several parameters, are given.
Optimal Prediction in Stochastic Regression Models with Application to the Analysis of Repeated Surveys
Authors: Tam S. M.
Published: February 2008

Several results relating to the optimal prediction of regression coefficients and random variables under a general linear model with stochastic coefficients are presented. These results are then applied to the analysis of repeated sample surveys over time. In particular, if the finite population can be modelled by a superpopulation model, a fully efficient method for the analysis of repeated surveys is proposed.
Statistical Significance: Balancing Evidence Against Doubt
Authors: Hall Peter , Selinger Ben
Published: February 2008

The notion of “statistical significance” is often used to quantify “reasonable doubt.” This paper briefly reviews the history of statistical significance. Scientific and legal approaches to the analysis of doubt are compared. Traditional scientific methods for describing error are shown to be comparatively stringent and inflexible. It is suggested that these attributes lead scientists to make firm value‐judgments about the quality of their own evidence. Those judgments may be inapplicable in other situations. This process of pre‐judging and censoring is surely undesirable when scientific evidence is presented in a wider context.
On a Simultaneous Characterization of the Poisson and Bernoulli Distributions
Authors: Kourouklis Stavros
Published: February 2008

Kimeldorf et al. (1981) established a simultaneous characterization of the Poisson and Bernoulli distributions. In this note two variants of the authors' characterizing condition are considered each of which is shown also to characterize simultaneously the Poisson and Bernoulli distributions.
Why Not Try a Robust Regression?
Authors: Hettmansperger THomas P.
Published: February 2008

We introduce and discuss three important regression diagnostics: leverage, Studentized residuals, and DFFITS. We then develop two approaches to bounded‐influence robust regression based on these diagnostics. The methods are illustrated on a data set using a simple MINITAB program.
On Tests for Equicorrelation Coefficient of a Standard Symmetric Multivariate Normal Distribution
Authors: SenGufta Ashis
Published: February 2008

Sampson (1976, 1978) has considered applications of the standard symmetric multivariate normal (SSMN) distribution and the estimation of its equi‐correlation coefficient, ρ. Tests for ρ are considered here. The likelihood ratio test suffers from several theoretical and practical shortcomings. We propose the locally most powerful (LMP) test which is globally (one‐sided) unbiased, very simple to compute and is based on the best natural unbiased estimator of ρ. Exact null and non‐null distributions of the test statistic are presented and percentage points are given. Statistical curvature (Efron, 1975) indicates that its performance improves with mk (sample size × dimension) while exact power computations show that even for reasonably small values of mk the performance is quite encouraging. Recalling Brown's (1971) cautions we establish by local comparison with the LMP similar test for ρ in the SMN (Rao, 1973) distribution, that here the additional information on the mean and variance is quite worthwhile.
On the Derivation of Efficiency Results in Linear Estimation
Authors: Rogers Alan J.
Published: February 2008

This paper proposes a simple rank condition for determining whether or not certain limited information estimators based on common data transformations in linear models are efficient. Examples which illustrate the use of the condition are presented.
Some Strategies of Two‐Stage Sampling for Estimating Population Ratios Over two Occasions
Authors: Okafor Fabian C. , Arnab Raghunath
Published: February 2008

summary

In this paper strategies based on a two‐stage successive sampling scheme are proposed for estimating the ratio of the population totals of two characters on the most recent occasion.

It is found that the proposed strategies perform better than the standard ratio when used in estimating the ratio of farmers' income to non‐farmers' income. But when applied to the estimation of ratio of girth to height of teak trees, a loss in efficiency is observed.
Nonparametric Inference for a Partially Observed Compartmental Process
Authors: Becker Niels , Yip Paul
Published: February 2008

Methods of nonparametric inference are proposed for a process with two transient and three absorbing states. It is assumed that the time of transitions between the transient states are unobservable. One area of applications is in epidemiology where the transient states correspond to healthy and ill, while the absorbing states correspond to types of death. It is the onset of illness which is not observable. An estimate is given for a cumulative hazard rate between the transient states, the exit hazard rates are estimated at a specific point in time and a statistic for comparing exit rates from the transient states is given.
Some Results for Uniformizable Semi‐Markov Processes
Authors: Kijima Masaaki
Published: February 2008

It is well known that finite Markov chains (M.C.s) in continuous time are uniformizable. That is, a finite M. C. in continuous time can be treated as an M. C. in discrete time with random Poisson transition epochs. In this paper, we see to what extent generalization of the uniformization to a class of semi‐Markov Processes (S.M.P.s) is possible. A necessary condition under which S.M.P.s are uniformizable is provided. It is shown that, an S.M.P. with dwell‐time distributions depending only on the current state is uniformizable if and only if the distributions are compound geometric distributions having the same base distribution. It is also shown that if the distributions are of generalized phase type then an S.M.P. being uniformizable implies that it is an M.C. in continuous time. Some properties that are shared by a uniformizable S.M.P. and the associated M.C. in discrete time are also discussed.
Confidence Intervals for Scale
Authors: Morgenthaler Stephan
Published: February 2008

This paper explains the approach to parameter estimation based on the idea of simultaneous models. Instead of using a single shape—as for example the normal distribution—a simultaneous model uses a finite number of distinct shapes F, G, etc. Such simultaneous systems are tools in gauging the finite sample behavior of estimators. And they can be applied in the design of an estimator with prescribed desirable properties.

The problem considered in this paper is interval estimation for a scale parameter. We discuss among other things the computation of optimal estimators in simultaneous models and study more closely the case of protecting against heavy‐tailed error distributions.
Bayes Arma Model Determination: Some Empirical Evidence
Authors: Poskitt D. S.
Published: February 2008

summary

In this paper the operational characteristics of a Bayesian procedure for autoregressive moving‐average model determination are considered. Finite sample bias is considered and the consequences of employing a data taper investigated.
ON THE BOOTSTRAP AND TWO‐SAMPLE PROBLEMS
Authors: Hall Peter , Martin Michael
Published: February 2008

summary

We present asymptotic theory for the bootstrap in two‐sample problems. If the samples are of sizesmandn, then our results show that one‐sided and two‐sided percentile‐tconfidence intervals have coverage errorO(m‐1+n‐1), and that symmetric two‐sided intervals have coverage errorO(m‐2+n‐1). Furthermore, coverage error of all percentile‐t intervals drops toO(m‐2+n‐2) when the populations the Normal. This decrease in error is also evidenced in a simulation study, and indicates that percentile‐tprovides a respectable solution to the Behrens‐Fisher problem. In addition we derive an explicit formula for the acceleration constant needed to implement accelerated bias‐correction in two‐sample problems.
ANALYSIS OF GENERALIZED LINEAR MODELS WITH NESTED STRATA OF VARIATION
Authors: Morton Richard
Published: February 2008

summary

A method of analysis by iteratively reweighted least squares is given for any generalized linear model with nested strata of variation due to errors in the linear predictor. It utilises the first order approximation of the effects of the errors.
NON‐ORTHOGONAL BLOCK STRUCTURE IN TWO‐PHASE DESIGNS
Authors: Wood J.T. , Williams E.R. , Speed T.P.
Published: February 2008

summary

A class of two‐phase designs is defined with the variance model exhibiting non‐orthogonal block structure. This class includes the two‐phase design treated in detail by both McIntyre (1955) and Curnow (1959). Results relating to the combinability of treatment estimators over strata and generalized least squares estimators are presented. A simple example illustrating non‐orthogonal block structure is used to provide some insight into the McIntyre (1955) two‐phase design.
OFFICIAL STATISTICS IN THE LATE COLONIAL PERIOD LEADING ON TO THE WORK OF THE FIRST COMMONWEALTH STATISTICIAN, G.H. KNIBBS
Authors: Heyde C.C.
Published: February 2008

summary

This paper begins with an overview of the development of official statistics in Australia in the late colonial period. It then leads on to provide an account of the contributions of the first Commonwealth Statistician, Sir George Handley Knibbs (1858–1929) which gives some emphasis to his scientific work and its international impact. Some material on the general historical and social background of the time is given to set the discussion in proper context.
A SURVEY OF EXPERIMENTAL DESIGN IN AUSTRALIA
Authors: Williams E.J.
Published: February 2008

summary

This paper surveys the research on Experimental Design carried out in Australia, or by Australians, from its inception in 1930 to the end of 1987. Some of the more important areas of design, and Australian contributions to each, are also discussed. The bibliography is intended as index to the important published work in this field.
NONPARAMETRIC RELIABILITY ESTIMATION BASED ON A FEW ORDERED OBSERVATIONS
Authors: Arsham H.
Published: February 2008

The usual one‐sided Kolmogorov‐Smirnov distance is generalized to obtain an improved lower confidence region for the extreme left tail of the reliability function based on k observations in a “k out of n censored” plan. Finite sample and asymptotic critical values necessary for implementation are given. The two numerical comparisons with existing parametric procedures for the case of complete or censored samples demonstrate the applicability of the proposed nonparametric procedure.
PROPERTIES OF THE PATTERNED VECH OPERATOR
Authors: McGilchrist C.A. , Cullis B.R.
Published: February 2008

The vec operator arranges the columns of a matrix one below the other. When the matrix is symmetric such elements are not distinct but an extraction of only the distinct elements on or below the diagonal forms the operation denoted by vech. For other types of patterned matrices a ‘patterned vech’ operator is defined. The transformations from vech to vec are not uniquely defined. Here we examine properties of linear transformations which overcome the lack of uniqueness and develop properties of such linear transformations.
A SIMPLE SEQUENTIAL WILCOXON TEST
Authors: Phatarfod R.M. , Sudbury Aidan
Published: February 2008

A simple sequential non‐parametric test for the two‐sample problem is proposed. A method of deriving its O.C. and A.S.N. funtions is given, and their adequacy confirmed by simulation. The test is found to require about 10 percent more observations than an optimal rank test; however it is much easier to apply. The test is found to be relatively robust.
VARIANCE ESTIMATION IN MULTI‐STAGE SAMPLING
Authors: Arnab R.
Published: February 2008

In multi‐stage sampling with the first stage units (fsu) chosen without replacement (WOR) with varying probability schemes (VPS) unbiased estimators (UE) of variances of homogeneous linear (HL) functions of unbiased estimators (UE) Ti's of fsu totals Yi's based on selection of subsequent stage units (SSU) from chosen fsu's are derived as homogeneous quadratic (HQ) functions of alternative less efficient UE's, say of Ti';'s of Yi's. Specific strategies are illustrated.
ASYMPTOTIC OPTIMALITY OF LIKELIHOOD RATIO TESTS FOR EXPONENTIAL DISTRIBUTIONS UNDER TYPE II CENSORING
Authors: Kourouklis Stavros
Published: February 2008

Consider the model of k two parameter exponential populations under a type II censoring scheme. In this paper we establish optimality in the sense of Bahadur of the likelihood ratio test for an arbitrary testing problem by requiring only Condition A in Hsieh (1979). This result unifies and generalizes the results in Samanta (1986).
KENDALL'S TAU AND CONTINGENCY TABLES
Authors: Brown B.M.
Published: February 2008

Kendall's tau is a coefficient of concordance between two rankings of n objects. Its definition and large sample normal approximation are easily extended to the case where one of the rankings contains ties. In this paper, definition and normal approximation are extended further to the case where both rankings contain ties. The results are applied to give a fully distribution‐free test for two‐way contingency tables with ordered categories.
A NOTE ON MULTIVARIATE LINEAR MODELS WITH NON‐ADDITIVITY
Authors: Kshirsagar Anant M.
Published: February 2008

Tukey's non‐additivity test in an analysis of variance model is extended to a multivariate linear model with covariates. If non‐additivity is found to exist, a Wilks's Lambda test for the dimensionality of the matrix of the non‐additivity parameters is derived and the Lambda criterion is then factorized into two independent test criteria to test meaningful hypotheses concerning the multivariate model.
INFERENCE ABOUT THE MEAN OF A POISSON DISTRIBUTION IN THE PRESENCE OF A NUISANCE PARAMETER
Authors: Yip Paul
Published: February 2008

In this note we examine the problem of estimating the mean of a Poisson distribution when a nuisance parameter is present. Using a condition of Cox (1958) about ancillarity in the presence of a nuisance parameter, we justify that inference about the parameter should be carried out using the conditional distribution given the appropriate ancillary statistics. A small simulation study has been done to compare the performance of the conditional likelihood approach and the standard likelihood approach.
ON A GENERAL DISTRIBUTION THEORY FOR A CLASS OF LIKELIHOOD RATIO CRITERIA
Authors: Gupta A.K. , Tang J.
Published: February 2008

In this paper the exact distribution of a statistic with general moment function has been derived in a gamma series and also in a beta series. It is shown that the Box expansion can be obtained from the gamma series by collecting terms of the same order.
THE REDUCTION OF RISKS FOR SET‐VALUED ESTIMATORS
Authors: Meister H. , Moeschlin O.
Published: February 2008

An extension of the Theorem of Rao‐Blackwell will be given for the case of set‐valued estimators, its images being nonempty, compact‐convex subsets of a certain Banach space. Moreover sufficiency will be characterized in connection with set‐valued estimators by related point‐valued functions.
THE UNEMPLOYMENT RATE WHEN THE LABOUR MARKET IS MODELLED BY A MARKOV CHAIN
Authors: Klebaner Fima C.
Published: February 2008

Assuming a Markov chain model for the labour market flow, we study it in its equilibrium state, We compare the observed and the theoretical unemployment rates. It is found that the observed unemployment rate approximates very closely the theoretical one. The mean and variance of the observed unemployment rate are computed. It is shown that its asymptotic distribution is normal.
JACKKNIFE TESTS FOR HETEROSCEDASTICITY IN THE GENERAL LINEAR MODEL
Authors: Giaccotto Carmelo , Sharma Subhash C.
Published: February 2008

In this paper, tests based on the Jackknife technique are proposed to test for heteroscedasticity in the linear regression model when the errors are non‐normal. These are the Jackknifed Goldfeld‐Quandt (GQ), and jack‐knife related variations of White (H), Lagrange multiplier (LM), Glejser (GL) and Bickel (B) tests. The power of the proposed tests is compared with that of GQ, H, LM, GL and B tests; and the robustness to the error distribution is analyzed under several heteroscedastic assumptions. The GQ test is by far the best test if the error distribution is close to normal, however, GQ test is not robust against non‐normal errors. By applying the jackknife technique to the regression a more robust statistic (GQJRG) is produced but the cost is a loss in power. The GQJRG statistic generally is not M powerful as the Bickel (BlOLS) and Glejser (GLlOLS) statistics.
DELAY ESTIMATION BY A HILBERT TRANSFORM METHOD
Authors: Nakano Junji , Tagami Shigemi
Published: February 2008

This paper describes an estimation of the time delay between two stationary time series signals, in which an input signal is measured with little noise and an output signal is the sum of a noise and the response from a linear system. We use the Hilbert transform relation for minimum delay systems to estimate the time delay. Some computer simulation results are given to evaluate the performance of the proposed method.
ESTIMATION OF THE CONDITIONAL PROBABILITY OF TUBERCULOSIS GIVEN THE RESPONSE OF A MANTOUX TEST
Authors: Hannah Murray , Becker Niels , Rich Jacob , Castle Charles
Published: February 2008

For the planning of community tuberculosis, prophylaxis one must know the prevalence of tuberculosis (TB) infection as a function of response to the Mantoux intradermal tuberculin test; the standard test for indicating Mycobacterium TB infection. The skin induration size used to select individuals for prophylaxis must be chosen carefully, in view of the costs associated with carrying out and supervising such prophylaxis.

The Mantoux test was used to obtain measurements on adolescents in metropolitan Victoria and on a small sample of adolescents with clinical TB. These data are employed to obtain estimates and to construct upper confidence bounds for the conditional probability of TB infection, given the level of Mantoux response. Two conservative methods are presented; one is ‘nonparametric’, the other ‘semiparametric’. The analyses indicate that for responses up to and including 13 mm, the probability of TB infection is less than.07 with ninety‐five percent confidence.
DECOMPOSITIONS FOR CONDITIONAL SYMMETRY MODEL INTO PALINDROMIC SYMMETRY AND MODIFIED MARGINAL HOMOGENEITY MODELS
Authors: Tomizawa Sadao
Published: February 2008

For square contingency tables with ordered categories, the conditional symmetry model is decomposed into the palindromic symmetry and the modified marginal homogeneity models, and moreover into the generalized palindromic symmetry model and two other models. The data on unaided vision first analysed by Stuart (1953, 1955) is analysed again by using the decompositions.
ON EMPIRICAL BAYES STOPPING TIMES
Authors: Karunamuni Rohan
Published: February 2008

We consider the empirical Bayes decision theory where the component problems are the optimal fixed sample size decision problem and a sequential decision problem. With these components, an empirical Bayes decision procedure selects both a stopping rule function and a terminal decision rule function. Empirical Bayes stopping rules are constructed for each case and the asymptotic behaviours are investigated.
UNBIASED ESTIMATION OF PARAMETRIC FUNCTIONS IN SAMPLING FROM TWO ONE‐TRUNCATION PARAMETER FAMILIES
Authors: Rohatgi Vijay K.
Published: February 2008

We consider the problem of minimum variance unbiased estimation of a U‐estimable function of two unknown truncation parameters based on independent random samples from two one‐truncation parameter families. In particular, we obtain the UMVU estimator of the probability that Y > X.
A SEQUENTIAL METHOD OF CONSTRUCTING OPTIMAL BLOCK DESIGNS
Authors: Zergaw Getachew
Published: February 2008

An algorithm for the construction of a wide class of block designs including Balanced Incomplete Blocks (BIB) is described. The algorithm which allows the experimenter to give weights for a set of treatment contrasts uses an initial starting design to generate an optimal block design sequentially. The performance of the algorithm is illustrated by examples, and designs constructed by the algorithm compare favourably with designs generated by other methods.
INVERSE GAUSSIAN CONTROL CHARTS
Authors: Edgeman Rick L.
Published: February 2008

summary

Control charts typically used to monitor process centrality and dispersion either assume normally distributed output or appeal to the viability of the central limit theorem. This appeal to the central limit theorem is frequently made on behalf of samples consisting of 10 or fewer items. Control charts for centrality and dispersion are presented for processes with inverse Gaussian distributed output.
A REMARK ON TESTING SIGNIFICANCE OF AN OBSERVED CORRELATION MATRIX
Authors: And Shande Chen , Mudholkar Govind S.
Published: February 2008

summary

A simple test for the diagonality of the covariance matrix of a multi‐variate normal population is proposed. The test, which is based upon the sum of squares of the z‐transforms of the sample correlations, is seen to compare well with the current tests in terms of both the null distribution approximations and the powers.
A RENEWAL THEOREM IN MULTIDIMENSIONAL TIME
Authors: Hagwood Charles
Published: February 2008

summary

Let Yl, Y2,… be i.i.d., positive, integer‐valued random variables with means, μ. Let the sequences {Yij, j= 1,2,…}, i= 1,…, r be independent copies of {Y1, Y2,…}. For n={n1,…, nr.}, n1≥1, let Sn=S̀n1k1=1= 1 …S̀nrkr=1 Yik1… Yrkr. We show that S̀Nk=1S̀∞k1=1…S̀∞nr=1 P[[Sn= k] ˜ [μ‐r N logr‐1 (N)/(r‐1)!] as N →∞.
THE SIGN TEST FOR STOCHASTIC PROCESSES
Authors: Huggins R.M.
Published: February 2008

summary

It is shown that the sign test may be applied to the residuals from the use of model fitting procedures, such as conditional least squares, to make inferences on the predictable part of a stochastic process. Minimal assumptions on the distribution of the process, apart from those already required for the model fitting procedure, are needed. The results are illustrated with an application to first order autoregressive processes.
ON THE EFFICIENCY OF THE QUASI‐LIKELIHOOD ESTIMATORS FOR EXPONENTIAL FAMILIES WITH EXTRA VARIATION
Authors: Morton R.
Published: February 2008

summary

Bounds are obtained for the asymptotic efficiency of the quasi‐likelihood estimator relative to the likelihood estimators for exponential families with random variables in the exponent. We conclude that the quasi‐likelihood is very efficient in the Poisson case for small means or small extra variation.
CONCOMITANT SCALE ESTIMATION IN REGRESSION PROBLEMS WITH INCREASING DIMENSION
Authors: Welsh A.H.
Published: February 2008

summary

We obtain Bahadur representations for the semi‐interquartile range and the median deviation when these estimators are based on the residuals from a linear regression model with increasing dimension. These representations yield a variety of central limit theorems and conditions under which the two estimators are equivalent. In particular, the representations justify the use of the estimators as concomitant scale estimators in general scale equivariant M‐estimation of a regression parameter when the dimension of the parameter increases with the sample size.