Confidence regions for the common mean vector of several multivariate normal populations

DOI10.2307/3315368zbMath0836.62040OpenAlexW1967763996MaRDI QIDQ4859244

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Publication date: 2 January 1996

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3315368

zbMATH Keywords

tablesconfidence regionmultivariate normal populationsaffine invariantweighted least squaresBehrens-Fisher problemGraybill-Deal estimatorminimal sufficient statisticmultiple comparison proceduretwo-sample caseindependent samplescombined estimatorcommon mean vectorcombined testpercentile points

Mathematics Subject Classification ID

Multivariate analysis (62H99) Estimation in multivariate analysis (62H12) Parametric tolerance and confidence regions (62F25) Point estimation (62F10) Statistical decision theory (62C99)

Related Items (8)

Comparison of Five Tests for the Common Mean of Several Multivariate Normal Populations ⋮ Estimation of means of multivariate normal populations with order restriction ⋮ Combining independent information in a multivariate calibration problem ⋮ Nonparametric Fusion Learning for Multiparameters: Synthesize Inferences From Diverse Sources Using Data Depth and Confidence Distribution ⋮ Generalized inferences on the common mean vector of several multivariate normal populations ⋮ Statistical inference for the common mean of two log-normal distributions and some applications in reliability ⋮ Inferences on the common mean of several inverse Gaussian populations ⋮ Inferences on the Common Mean of Several Normal Populations Based on the Generalized Variable Method

Uses Software

• AS 53

Cites Work

• Two inequalities with an application
• On estimating a common multivariate normal mean vector
• Estimating the common mean of two multivariate normal distributions
• Estimation of a common multivariate normal mean vector
• Point and confidence estimation of a common mean and recovery of interblock information
• Estimating the common mean of several normal populations
• Combining independent tests in multivariate linear models
• Shrinkage domination in a multivariate common mean problem
• Interval estimation of the common mean
• Estimation of location parameters from two linear models under normality
• Combining Independent Tests in Linear Models
• Combining Unbiased Estimators

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