Double shrink methodologies to determine the sample size via covariance structures

DOI10.1016/J.JSPI.2008.03.032zbMath1149.62018OpenAlexW2005941195MaRDI QIDQ958760

Makoto Aoshima, Kazuyoshi Yata

Publication date: 8 December 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2241/101289

zbMATH Keywords

optimal sample sizetwo-stage samplingintraclass correlation modelasymptotic uniformity

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Parametric tolerance and confidence regions (62F25) Point estimation (62F10)

Related Items (4)

Inference on high-dimensional mean vectors with fewer observations than the dimension ⋮ Two-Stage Procedures for Estimating the Difference of Means when the Sampling Cost is Different ⋮ Effective Two-Stage Estimation for a Linear Function of High-Dimensional Gaussian Means ⋮ Two-Stage Procedures for High-Dimensional Data

Cites Work

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• Asymptotic second-order consistency for two-stage estimation methodologies and its applications
• Asymptotic theory of triple sampling for sequential estimation of a mean
• On a two-stage procedure having second-order properties with applications
• Asymptotic Second-Order Efficiency of a Two-Stage Procedure for Estimating a Linear Function of Normal Means
• Second-Order Efficiency for Two-Stage Estimation of a Linear Function of Normal Mean Vectors when Covariance Matrices Have Some Structures
• A Two-Sample Test for a Linear Hypothesis Whose Power is Independent of the Variance

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