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Sample Size Savings for Curtailed One-Sample Nonparametric Tests for Location Shift

提前终止的单样本非参数位置偏移检验能节省多少样本

Asymptotic moments of normed sample size savings are derived for one-sided curtailed nonparametric tests for symmetry for testing location shift hypotheses under the null hypothesis and contiguous alternatives. The contiguous alternative results are derived using Feller's (1943) central limit theorem result for large deviations and techniques used in Albers, Bickel and van Zwet (1976).

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Missing Data in the One-Population Multivariate Normal Patterned Mean and Covariance Matrix Testing and Estimation Problem

缺失数据下单总体多元正态结构化均值与协方差的检验和估计

In this paper the multivariate normal linear patterned mean and covariance matrix testing and estimation problem is studied in the presence of missing data for general one-population hypotheses. The Newton-Raphson, Method of Scoring and EM algorithms are given for finding the maximum likelihood estimates. The asymptotic joint distribution of the maximum likelihood estimates under null and alternative hypotheses are derived along with the form of the likelihood ratio…

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Finding Maximum Likelihood Estimates of Patterned Covariance Matrices by the EM Algorithm

用 EM 算法求解结构化协方差矩阵的最大似然估计

Some patterned covariance matrices used to model multivariate normal data that do not have explicit maximum likelihood estimates can be viewed as submatrices of larger patterned covariance matrices that do have explicit maximum likelihood estimates. In such cases, the smaller covariance matrix can be viewed as the covariance matrix for observed variables and the larger covariance matrix can be viewed as the covariance matrix for both observed and missing variables. The…

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Finding maximum likelihood estimates of patterned covariance matrices by the EM algorithm

利用 EM 算法求结构化协方差矩阵的极大似然估计

Some patterned covariance matrices used to model multivariate normal data that do not have explicit maximum likelihood estimates can be viewed as submatrices of larger patterned covariance matrices that do have explicit maximum likelihood estimates. In such cases, the smaller covariance matrix can be viewed as the covariance matrix for observed variables and the larger covariance matrix can be viewed as the covariance matrix for both observed and missing variables. The…

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Explicit Maximum Likelihood Estimates from Balanced Data in the Mixed Model of the Analysis of Variance

平衡混合方差分析模型中的显式最大似然估计

A result of Szatrowski, giving necessary and sufficient conditions for the existence of explicit maximum likelihood estimates for multivariate normal means and covariances with linear structure, can be applied to the problem of obtaining explicit maximum likelihood estimates in the mixed model of the analysis of variance. This application yields a simple procedure for checking whether or not explicit maximum likelihood estimates exist for the parameters in the balanced mixed…

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Necessary and Sufficient Conditions for Explicit Solutions in the Multivariate Normal Estimation Problem for Patterned Means and Covariances

结构化均值与协方差多元正态估计中显式解的充要条件

The problem of finding maximum likelihood estimates for patterned means and covariance matrices in multivariate analysis is considered. Necessary and sufficient conditions are presented for the existence of explicit solutions and the obtaining of these explicit solutions in one iteration of the scoring equations from any positive definite starting point. Cases in which averaging yields the explicit maximum likelihood estimates are discussed. These results can be applied to…

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Asymptotic Nonnull Distributions for Likelihood Ratio Statistics in the Multivariate Normal Patterned Mean and Covariance Matrix Testing Problem

多元正态结构化均值与协方差检验中似然比统计量的非零假设渐近分布

The multivariate normal patterned mean and covariance matrix testing problem is studied for general one and $k$-population hypotheses. T. W. Anderson's iterative algorithm for finding the maximum likelihood estimates, the forms of the likelihood ratio tests, and asymptotic chi-square distributions of these tests under the null hypothesis are given. The nonnull asymptotic normal distribution is derived using the standard delta method. This derivation involves using several…

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