bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quota fulfillment times
Authors: Anderson Keaven , Sobel Milton , Uppuluri V. R. R. 
Published: June 2006

AbstractAn example of the classical occupancy problem is to sample with replacement from an urn containing several colours of balls and count the number of balls sampled until a given number of “quotas” are filled. This and the corresponding random variable for sampling without replacement will be referred to as quota fulfillment times. Asymptotic and exact methods for computing moments and distributions are given in this paper. Moments of quota fulfillment times are related to moments of order statistics of beta and gamma random variables. Most of the results for sampling without replacement and some of the results for sampling with replacement are believed to be new. Some other known sampling‐with‐replacement results are given for comparative purposes.
A note on multivariate linear exponential distributions
Authors: Doss D.C. 
Published: June 2006

AbstractA distribution admitting the moment generating function (mgf) is a member of one and only one linear exponential family Pμ = {Pω:ω ϵ Ωμ} with dPω(x) = {eω'x/f(ω)} dμ(x). Factorization of the mgf of a member of a linear exponential family into a finite number of mgf's of linear exponential distributions, implies such a factorization for all members of the family. Consequently, infinite divisibility of the mgf of a member of a linear exponential family implies infinite divisibility for all members of the family.
A characterization of the general mean
Authors: Weerahandi Samaradasa , Zidek James V. 
Published: June 2006

AbstractA characterization is given of the general mean which is (∂Xp)1/p or exp[log X] for X > 0 according as ρ ≠0 or ρ = 0, where ρ is an unspecified parameter. The approach is axiomatic. The general mean is defined as any quantity satisfying certain axioms which embrace the minimal requirements that any reasonable candidate for the role of mean or most typical value should satisfy. The quantity, indexed by p and given above, is uniquely implied by these axioms.
Comparison of efficient L‐ and R‐estimators of location
Authors: Froda Sorana 
Published: June 2006

AbstractScholz (1974) proved that the asymptotic variance of an R‐estimator of location is no larger than that of an L‐estimator when the observations come from a distribution G different from the distribution F for which the two estimators are efficient. This note extends this result to distributions F whose density has a first but no second derivative.
Effect of correlation on the estimation of a mean in the presence of spurious observations
Authors: Guttman Irwin , Tiao G. C. 
Published: June 2006

AbstractThis paper examines the effect of correlation of observations on estimators of a mean which are designed to guard against the possibility of spurious observations (that is, observations generated in a manner not intended). The mean squared error, premium and protection of these estimators are evaluated and discussed for some specific correlation structures.
Statistical issues in epidemiologic studies of the health effects of ambient acid aerosols
Authors: Ware James H. , Stram Daniel O. 
Published: June 2006

AbstractAlthough the ecologic effects of acid rain have been widely reported, relatively little is known about the effects of acidic air pollution on human health. Some epidemiologic and animal studies suggest, however, that acidity is an important determinant of the respiratory health effects of aerosols. This paper reviews some of that evidence and discusses its implications for the design and analysis of epidemiologic studies. We contrast two types of exposure patterns: peak exposures associated with air pollution episodes, and chronic exposures resulting from persistently high levels of air pollutants. Recent work on the analysis of repeated categorical outcome variables provides new methods for the analysis of episode studies. Studies of long‐term exposure require comparisons among population groups, and these comparisons can be subject to the design effects characteristic of multistage sample surveys. We examine the implications of these design effects for epidemiologic studies. Finally, the paper discusses the measurement errors induced by the use of outdoor measurements to quantify personal exposure to air pollutants. Recent work on methods for errors‐in‐variables problems may aid in assessing the effects of such errors on conventional analyses of air‐pollution studies.
Criteria for the equality between ordinary least squares and best linear unbiased estimators under certain linear models
Authors: Baksalary Jerzy K. 
Published: June 2006

AbstractA new necessary and sufficient condition is derived for the equality between the ordinary least‐squares estimator and the best linear unbiased estimator of the expectation vector in linear models with certain specific design matrices. This condition is then applied to special cases involving one‐way and two‐way classification models.
Lightning detection in British Columbia: An example of using system operation at unknown reliability to estimate component reliability
Authors: Johnson Bruce R. 
Published: June 2006

AbstractLightning data collected over three dry seasons from the detection system operated by the British Columbia Ministry of Forests were analyzed to estimate the distribution of lightning signal strength and component detection efficiencies. The analysis was based on more than 165,000 lightning‐strike records, where component detectors served both as lightning finders and as data collectors for evaluating the performance of other component detectors in the network. In spite of the unusual feature of this application involving a system evaluating itself, much was revealed to identify weaknesses and suggest improvements. A postanalysis system‐modification update is included.
Jackknifing L‐estimates
Authors: Cheng Kuang‐Fu 
Published: June 2006

AbstractLinear functions of order statistics (“L‐estimates”) of the form Tn =under jackknifing are investigated. This paper proves that with suitable conditions on the function J, the jackknifed version Tn of the L‐estimate Tn has the same limit distribution as Tn. It is also shown that the jackknife estimate of the asymptotic variance of n1/2 is consistent. Furthermore, the Berry‐Esséen rate associated with asymptotic normality, and a law of the iterated logarithm of a class of jackknife L‐estimates, are characterized.
THE non‐null distribution of the likelihood ratio criterion for testing the hypothesis that the covariance matrix is diagonal
Authors: Mathai A.M. , Tan W.Y. 
Published: June 2006

AbstractThis article deals with the exact non‐null distribution of the likelihood ratio criterion for testing the hypothesis that the covariance matrix in a multinormal distribution is diagonal. The exact non‐null moments as well as the exact non‐null distribution are derived. The distribution is also expressed in computable form with the help of inverse Mellin transform and calculus of residues. The results obtained in this article are useful in studying the power of testing several correlation coefficients simultaneously.
A distribution‐free approach to qdantal response assays
Authors: Shuster Jonathan J. , Yang Mark C. K. 
Published: June 2006

AbstractA nonparametric method is developed to estimate the minimum dosage level required to induce a given response rate in an experiment. The only assumption used about the response rate is that it is a nondecreasing function with respect to the dosage level. Let nisubjects be independently tested at dosage level xix1x2xk. This paper presents methodology for the estimation of the smallest i such that the response probability at xi is no less than a required level p. A comparison with well‐known nonparametric methods shows that this method is better in some cases. A design of minimum required sample size for a given accuracy is also developed.
LOI conditionnelle de la statistique d'ordre 1 $dcun echantillon: Application
Authors: Colin Bernard 
Published: June 2006

AbstractA propos $dCun algorithme utilis$eA en recherche op$eArationnelle, nous tenterons $dC$eAtablir une d$eApendance, entre la somme de n observations ind$eApendantes d'une variable al$eAatoire et le minimum de ces observations.
Bootstrap and other methods to measure errors in survey estimates
Authors: Kovar J. G. , Rao J. N. K. , Wu C. F. J. 
Published: June 2006

AbstractVariance estimation techniques for nonlinear statistics, such as ratios and regression and correlation coefficients, and functionals, such as quantiles, are reviewed in the context of sampling from stratified populations. In particular, resampling methods such as the bootstrap, the jackknife, and balanced repeated replication are compared with the traditional linearization method for nonlinear statistics and a method based on Woodruff's confidence intervals for the quantiles. Results of empirical studies are presented on the bias and stability of these variance estimators and on confidence‐interval coverage probabilities and lengths.
Estimating the variance of raking‐ratio estimators
Authors: Binder D. A. , Théberge A. 
Published: June 2006

AbstractThis paper is concerned with the asymptotic properties of the converged solution of the raking‐ratio estimator. After a description of the raking‐ratio estimation procedure, we show that the estimator can be unbiased in the presence of nonresponse if the nonresponse has a particular structure. We also give the asymptotic variance of the estimator. Finally, the results of two numerical applications are presented.
Application des séries chronologiques à l'étude des révisions
Authors: Lefrançois Bernard 
Published: June 2006

AbstractTime series analysis is applied to the revisions made to a subset of the Canadian National Accounts, in order to determine if, and how, the preliminary figures currently released can be improved toward the first annually figures. Better estimates of period‐to‐period change could thus be obtained. The main findings are that the preliminary figures could be improved, and that this would follow from a modification to the benchmarking methods.An English version of this paper is available upon request.
Use of questions on activities of daily living to screen for disabled persons in a household survey
Authors: Binder David A. , Morin Jean‐Pierre 
Published: June 2006

AbstractIn recent years, there has been increasing interest in conducting surveys to establish baseline data on the needs and characteristics of the disabled. To respond to this demand, Statistics Canada launched a program in 1982 to survey this population. Several surveys have since been conducted, using as a screening criterion for potentially disabled persons an adaptation of the Activities of Daily Living (ADLs), first developed by the Organization for Economic Co‐operation and Development (OECD). Other health‐related surveys have also been conducted which have incorporated these same ADLs, but not for the express purpose of conducting a survey of the disabled. Whereas these separate surveys had many commonalities, there were certain important differences, which led to remarkably different screening rates. In this paper we study in detail the nature of these differences. We suggest a number of factors which can seriously affect the rates of screening, one of which is the mode of data collection, especially with respect to whether the survey contains additional components which are directed at obtaining information on the disabled.
Partial differential equations for hypergeometric functions 3F2 of matrix argument
Authors: Fujikoshi Yasunori 
Published: June 2006

AbstractMany multivariate non‐null distributions and moment formulas can be expressed in terms of hypergeometric functions pFq of matrix arqument. Muirhead [6] and Constantine and Muirhead [2] gave partial differential equations for the functions of 2F1 of one argument matrix and two argument matrices, respectively. Such differential equations have been used to obtain asymptotic expansions of the functions (Muirhead [7], [8], [9], Sugiura [10]). The purpose of this paper is to derive partial differential equations for the functions 3F2 (a1 a2, a3; b1, b2, R) and 3F2 (a1, a2, a3; b1, b2; R, S). Differential equations for 2F2 are also obtained.
Bayesian estimates of predictive value and related parameters of a diagnostic test
Authors: Viana Ma G. , Ramakrishnan V. 
Published: June 2006

AbstractBayesian analysis of predictive values and related parameters of a diagnostic test are derived. In one case, the estimates are conditional on values of the prevalence of the disease; in the second case, the corresponding unconditional estimates are presented. Small‐sample point estimates, posterior moments, and credibility intervals for all related parameters are obtained. Numerical methods of solution are also discussed.
Strong invariance principles for triangular arrays of weakly dependent random variables
Authors: Dabrowski Andre Robert , Zoglat Abdelhak 
Published: June 2006

AbstractWe establish a strong invariance principle for triangular arrays of a broad class of weakly dependent real random variables. We approximate the original array of dependent random variables by an array of rowwise independent standard normal variables. We demonstrate the functional central limit theorem and law of the iterated logarithm for the approximating array and thereby extend these results to the original array. Among several examples, we look at arrays used in describing the rate of convergence of estimators in regression analysis.
Modifications of the Mack‐Wolfe umbrella tests for a generalized Behrens‐Fisher problem
Authors: Chen Y. I. , Wolfe D. A. 
Published: June 2006

AbstractWe are concerned with testing procedures for umbrella alternatives in the k‐sample location problem without making the assumption that the underlying populations have the same shape. Modifications of the Mack‐Wolfe tests are proposed for the cases when the peak of the umbrella is known or unknown. The proposed procedures are exactly distribution‐free when the continuous populations have the same shape. The modified test for peak‐known umbrella alternatives remains asymptotically distribution‐free when the continuous populations are symmetric, but not necessarily with the same shape.
A complete solution to the problem of robustness of Grubbs's test
Authors: Baksalary Jerzy K. , Puntanen Simo 
Published: June 2006

AbstractSrivastava (1980) showed that Grubbs's test for detecting a univariate outlier is robust against the effect of intraclass correlation structure. Young, Pavur, and Marco (1989) extended this result by proving that both the significance level and the power of Grubbs's test remain unchanged within a wider family of dispersion matrices, introduced by Baldessari (1966) in a different context. In this note, we derive a complete solution of the problem by establishing that the characteristics of Grubbs's test are invariant with respect to a given dispersion matrix if and only if it has Baldessari's structure.
On prediction and mean squared error
Authors: Yatracos Yannis G. 
Published: June 2006

AbstractPractical questions motivate the search for predictors either of an as yet unobserved random vector, or of a random function of a parameter. An extension of the classical UMVUE theory is presented to cover such situations. In includes a Rao‐Blackwell‐type theorem, a Cramer‐Rao‐type inequality, and necessary and sufficient conditions for a predictor to minimize the mean squared error uniformly in the parameter. Applications are considered to the problem of selected means, the species problem, and the examination of some u‐v estimates of Robbins (1988).
Inequalities for the partial sums of elliptical order statistics related to genetic selection
Authors: Fang Kai‐Tai , Liang Jia‐Juang 
Published: June 2006

AbstractLet X1,…,Xn be exchangeable normal variables with a common correlation p, and let X(1) > … > X(n) denote their order statistics. The random variable σni=n—k+1xi, called the selection differential by geneticists, is of particular interest in genetic selection and related areas. In this paper we give results concerning a conjecture of Tong (1982) on the distribution of this random variable as a function of ρ. The same technique used can be applied to yield more general results for linear combinations of order statistics from elliptical distributions.
Asymptotic optimality of a class of rank tests for replicated latin‐square designs
Authors: Monga E. , Tardif S. 
Published: June 2006

AbstractThis paper is concerned with the class of conditionally distribution‐free rank tests introduced by Monga and Tardif (1994) for replicated Latin‐square designs. It is possible to proceed with an enlargement of this class by making use of the method of ranking after substitution. The unconditional asymptotic behaviour of any member of the enlarged class is derived under the null hypothesis of no treatment effects as well as under a sequence of contiguous alternatives. This enables the establishment of the asymptotic Pitman efficiency of any member relative to the asymptotically minimax test and to conclude that at least one member of the class is asymptotically as efficient as the latter.
Convergence rates of change‐point estimators and tail probabilities of the first‐passage‐time process
Authors: Baron Michael 
Published: June 2006

AbstractIn the classical setting of the change‐point problem, the maximum‐likelihood estimator and the traditional confidence region for the change‐point parameter are considered. It is shown that the probability of the correct decision, the coverage probability and the expected size of the confidence set converge exponentially fast as the sample size increases to infinity. For this purpose, the tail probabilities of the first passage times are studied. General inequalities are established, and exact asymptotics are obtained for the case of Bernoulli distributions. A closed asymptotic form for the expected size of the confidence set is derived for this case via the conditional distribution of the first passage times.
On the relation between Hodges‐Lehmann efficiency and Pitman efficiency
Authors: Kourouklis Stavros 
Published: June 2006

AbstractThe relation between Hodges–Lehmann efficiency and Pitman efficiency is studied in the context of testing one‐sided hypotheses about a real‐valued parameter. It is first shown that for tests based on sums of independently and identically distributed observations local Hodges‐Lehmann efficiency is equivalent to Pitman efficiency. Then, it is proved that this equivalence also carries over to tests based on two broad classes of M ‐estimators for the location problem. In all cases considered explicit formulas of the Hodges‐Lehmann efficacies are obtained.
First‐passage densities of controlled Gaussian processes
Authors: Lefebvre Mario 
Published: June 2006

AbstractWhittle has proved a theorem that gives the optimal control of Gaussian processes in terms of the mathematical expectation of a function of the time and the place where the uncontrolled processes hit the boundary of the stopping region for the first time. In this paper we obtain formulae for the joint probability density function of the first hitting time and place and, in the time‐invariant case, for the moment generating function of the first exit time of the optimally controlled processes. Two particular one‐dimensional cases are considered.
Bounded‐influence rank estimation in the linear model
Authors: Wiens Douglas , Zhou Julie 
Published: June 2006

AbstractWe introduce and study a class of rank‐based estimators for the linear model. The estimate may be roughly described as being calculated in the same manner as a generalized M‐estimate, but with the residual being replaced by a function of its signed rank. The influence function can thus be bounded, both as a function of the residual and as a function of the carriers. Subject to such a bound, the efficiency at a particular model distribution can be optimized by appropriate choices of rank scores and carrier weights. Such choices are given, with respect to a variety of optimality criteria. We compare our estimates with several others, in a Monte Carlo study and on a real data set from the literature.
Asymptotic distributions of functions of a sample covariance matrix under the elliptical distribution
Authors: Iwashita Toshiya , Siotani Minoru 
Published: June 2006

AbstractThis paper is concerned with asymptotic distributions of functions of a sample covariance matrix under the elliptical model. Simple but useful formulae for calculating asymptotic variances and covariances of the functions are derived. Also, an asymptotic expansion formula for the expectation of a function of a sample covariance matrix is derived; it is given up to the second‐order term with respect to the inverse of the sample size. Two examples are given: one of calculating the asymptotic variances and covariances of the stepdown multiple correlation coefficients, and the other of obtaining the asymptotic expansion formula for the moments of sample generalized variance.
Efficiency of reduced logistic regression models
Authors: Bull Shelley B. , Greenwood Celia M.T. , Donner Allan 
Published: June 2006

AbstractOne feature of the usual polychotomous logistic regression model for categorical outcomes is that a covariate must be included in all the regression equations. If a covariate is not important in all of them, the procedure will estimate unnecessary parameters. More flexible approaches allow different subsets of covariates in different regressions. One alternative uses individualized regressions which express the polychotomous model as a series of dichotomous models. Another uses a model in which a reduced set of parameters is simultaneously estimated for all the regressions. Large‐sample efficiencies of these procedures were compared in a variety of circumstances in which there was a common baseline category for the outcome and the covariates were normally distributed. For a correctly specified model, the reduced estimates were over 100% efficient for nonzero slope parameters and up to 500% efficient when the baseline frequency and the effect of interest were small. The individualized estimates could have efficiencies less than 50% when the effect of interest was large, but were also up to 130% efficient when the baseline frequency was large and the effect of interest was small. Efficiency was usually enhanced by correlation among the covariates. For an underspecified reduced model, asymptotic bias in the reduced estimates was approximately proportional to the magnitude of the omitted parameter and to the reciprocal of the baseline frequency.
On‐line control procedures under the random‐walk model with measurement error and attribute observations
Authors: Srivastava M.S. , Wu Yanhong 
Published: June 2006

AbstractAssuming the quality characteristic process follows the random‐walk model, the economic online control procedures are investigated by using the boundary correction technique when (1) the noise or measurement error follows either the random‐walk model or the pure random model, and (2) the observations are taken by attributes only. Simple approximations for the long‐run cost rate and optimal‐control parameters are obtained.
On the Edgeworth expansion and bootstrap approximation for the cox regression model under random censorship
Authors: Gu Minggao 
Published: June 2006

AbstractWe establish the one‐term Edgeworth expansion for various statistics related to Cox semipara‐metric regression model when the covariate is one‐dimensional and the observations are i.i.d. We show that the bootstrap approximation method is second‐order correct. The second‐order‐correct estimates of the sampling distribution can be obtained without Monte Carlo simulation. We pay special attention to the Studentized version of the statistics and show that their distributions are different from those of the original statistics to order n‐½