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Second-Order Pitman Closeness and Pitman Admissibility

二阶 Pitman 接近性与 Pitman 可容许性

Motivated by the first-order Pitman closeness of best asymptotically normal estimators and some recent developments on higher-order asymptotic efficiency of estimators, a second-order asymptotic theory is developed for comparison of estimators under the Pitman closeness criterion, covering both the cases without and with nuisance parameters. The notion of second-order Pitman admissibility is also developed.

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Pitman's Measure of Closeness: A Comparison of Statistical Estimators.

皮特曼接近性度量:统计估计量的比较

Preface Part I. Introduction 1. Evolution of Estimation Theory Least Squares Method of Moments Maximum Likelihood Uniformly Minimum Variance Unbiased Estimation Biased Estimation Bayes and Empirical Bayes Influence Functions and Resampling Techniques Future Directions 2. PMC Comes of Age PMC: A Product of Controversy PMC as an Intuitive Criterion 3. The Scope of the Book History, Motivation, and Controversy of PMC A Unified Development of PMC Part II. Development of Pitman's…

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Comparison of Linear Estimators Using Pitman's Measure of Closeness

利用Pitman接近性准则比较线性估计量

A method is given for the comparison of two linear forms of a common random vector under the criterion of Pitman's measure of closeness. Assuming multivariate normality of the random vector, one can determine exact expressions for the closeness probabilities. The applicability of the theory is illustrated on the comparison of ridge regression estimators.

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Improved Estimation in a Contingency Table: Independence Structure

利用独立性结构改进列联表概率估计

Estimation of the cell probabilities in a two-way contingency table is considered when it is plausible that the table might have an independence structure relating to the two traits. In a classical nonparametric setup, the unrestricted maximum likelihood estimators of the cell probabilities are the corresponding sample proportions; under the assumption of independence, the restricted estimators are the product of the respective row and column sample proportions. The latter…

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Inference Based on Ranks for the Multiple-Design Multivariate Linear Model

多设计多元线性模型的秩推断

Multivariate models more general than the standard multivariate linear model have received considerable attention in both the statistical and econometric literature; see Srivastava (1966, 1967, 1968) and Kleinbaum (1973). The multiple-design multivariate (MDM) linear model generalizes the standard multivariate linear model in the sense that a different design matrix is used for each response (dependent) variable. Important applications of the MDM linear model include…

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Improved Estimation in a Contingency Table: Independence Structure

利用独立结构改进列联表概率估计

Estimation of the cell probabilities in a two-way contingency table is considered when it is plausible that the table might have an independence structure relating to the two traits. In a classical nonparametric setup, the unrestricted maximum likelihood estimators of the cell probabilities are the corresponding sample proportions; under the assumption of independence, the restricted estimators are the product of the respective row and column sample proportions. The latter…

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Sequential Shrinkage Estimation

序贯收缩估计

The paper develops a class of James-Stein estimators that dominates the sample mean under sequential sampling schemes of Ghosh, Sinha and Mukhopadhyay (1976). Asymptotic risk expansions of the sample mean and James-Stein estimators are provided up to the second-order term. Also, a Monte Carlo study is undertaken to compare the risks of these estimators.

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Union-Intersection Rank Tests for Ordered Alternatives in ANOCOVA

协方差分析中有序备择的并交秩检验

For an analysis of covariance model (pertaining to completely randomized as well as complete block designs) based on the union-intersection principle, a general class of permutationally distribution-free rank tests for the ordered alternative problem is considered. The theory is supplemented by numerical studies.

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Union-Intersection Rank Tests for Ordered Alternatives in ANOCOVA

协方差分析中有序备择的并交秩检验

For an analysis of covariance model (pertaining to completely randomized as well as complete block designs) based on the union-intersection principle, a general class of permutationally distribution-free rank tests for the ordered alternative problem is considered. The theory is supplemented by numerical studies.

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Statistical Inference for Censored Bivariate Normal Distributions Based on Induced Order Statistics

基于诱导次序统计量的删失二元正态分布推断

For a censored sample from a bivariate normal distribution consisting of the firstk ofn order statistics of one variable and the induced order statistics of the other variable, the maximum likelihood estimators of the parameters and the associated large sample co-variance matrix are derived. The likelihood ratio test for independence is also given and its power properties studied. These methods are useful in selection problems or in life testing situations in which…

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Statistical inference for censored bivariate normal distributions based on induced order statistics

基于伴随次序统计量的删失二元正态分布推断

For a censored sample from a bivariate normal distribution consisting of the firstk ofn order statistics of one variable and the induced order statistics of the other variable, the maximum likelihood estimators of the parameters and the associated large sample co-variance matrix are derived. The likelihood ratio test for independence is also given and its power properties studied. These methods are useful in selection problems or in life testing situations in which…

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The Locally Optimal Combination of Independent Test Statistics

独立检验统计量的局部最优组合

A class of locally optimal tests based on linear functions of certain transformations of independent test statistics is proposed and studied. These overall tests are useful in combining independent tests for certain multivariate or multiparameter hypotheses where local optimality is interpreted in a specialized sense. For the two-sample case, along with the expressions for the null distributions of the test statistics, tabulations of percentile points are provided.

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The Locally Optimal Combination of Independent Test Statistics

独立检验统计量的局部最优组合

A class of locally optimal tests based on linear functions of certain transformations of independent test statistics is proposed and studied. These overall tests are useful in combining independent tests for certain multivariate or multiparameter hypotheses where local optimality is interpreted in a specialized sense. For the two-sample case, along with the expressions for the null distributions of the test statistics, tabulations of percentile points are provided.

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