Testing multinormality based on low-dimensional projection
type: Item
instance of: scholarly article
title: Testing multinormality based on low-dimensional projection
zbMATH Open document ID: 0961.65005
DOI: 10.1016/S0378-3758(99)00168-8
author: Hong-Bin Fang
author: Kai-Tai Fang
author: Jiajuan Liang
author: Runze Li
published in: Journal of Statistical Planning and Inference
publication date: 2000-12-14T00:00:00Z
review text: The aim of this paper is to construct projection tests for multivariate normality by making use of affine invariant statistics. These statistics can be used for arbitrary dimension \(d\) even in the case when the sample size \(n\leq d\). The construction is essentially based on properties of left-spherical matrix distributions. A practical example is analyzed.
Mathematics Subject Classification ID: 65C60
Mathematics Subject Classification ID: 62G10
Mathematics Subject Classification ID: 62H15
Mathematics Subject Classification ID: 65C05
zbMATH DE Number: 1436961
zbMATH Keywords: numerical example
zbMATH Keywords: left-spherical matrix distribution
zbMATH Keywords: Mardia's skewness and kurtosis
zbMATH Keywords: projection test
zbMATH Keywords: testing multinormality
zbMATH Keywords: affine invariant statistics
reviewed by: Radu Theodorescu
MaRDI profile type: Publication
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Wikidata QID: Q127227053
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description: scientific article; zbMATH DE number 1436961