The asymptotic variance matrix of the sample correlation matrix
type: Item
instance of: scholarly article
title: The asymptotic variance matrix of the sample correlation matrix
zbMATH Open document ID: 0716.62025
DOI: 10.1016/0024-3795(90)90363-H
author: Heinz Neudecker
author: A. M. Wesselman
published in: Linear Algebra and its Applications
publication date: 1990-01-01T00:00:00Z
review text: Asymptotic distributions of sample covariance and sample correlation matrices are derived using the population-sample decomposition method [first published by \textit{B. M. S. van Praag}, \textit{J. de Leeuw} and \textit{T. Kloek}, Appl. Stochastic Models Data Anal. 2, 99-119 (1986; Zbl 0628.62052), and \textit{B. M. S. van Praag} and \textit{B. Wesselman}, Comput. Stat. Q. 1, 205-231 (1984; Zbl 0614.62078)]. The derivation uses the classic Lindeberg-Lévy central limit theorem and for this problem very well fitting notations and tools of matrix theory. The history of the problem is discussed, too.
Mathematics Subject Classification ID: 62E20
Mathematics Subject Classification ID: 60F05
Mathematics Subject Classification ID: 62H10
Mathematics Subject Classification ID: 62H20
zbMATH DE Number: 4180543
zbMATH Keywords: covariance matrix
zbMATH Keywords: sample correlation matrices
zbMATH Keywords: population-sample decomposition method
zbMATH Keywords: Lindeberg-Lévy central limit theorem
reviewed by: Jan Ámos Víšek
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 4180543