On a Class of Multivariate Multisample Rank Order Tests II (Classic Reprint)

Madan Lal Puri, Pranab Kumar Sen

ISBN 10: 1333220839 / ISBN 13: 9781333220839

Published by Forgotten Books, 2022

About this Item

Print on Demand. This book introduces a class of rank order tests for homogeneity of dispersion matrices in multivariate analysis. Most nonparametric tests for multivariate analysis are restricted to location and scale problems, or patterns of association. The author presents both permutationally distribution-free tests assuming the identity of location parameters, and large-sample tests without assuming location parameter identity. They also briefly discuss the problem of testing simultaneously the homogeneity of location parameters as well as dispersion matrices. The tests proposed by the author are extensions of the Chernoff-Savage type of statistics, and the corresponding rank order estimates are used to formulate the tests. The book concludes with a discussion of the asymptotic properties of the tests, including asymptotic normality and asymptotic relative efficiency, making it a valuable resource for researchers and practitioners working in multivariate analysis and nonparametric inference. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book.

Seller Inventory # 9781333220839_0

Bibliographic Details

• Title: On a Class of Multivariate Multisample Rank Order Tests II (Classic Reprint)
• Publisher: Forgotten Books
• Publication Date: 2022
• Language: English
• ISBN 10: 1333220839
• ISBN 13: 9781333220839
• Binding: Paperback
• Condition: New
• Book Type: print-on-demand item
• Seller catalogs:
  • Statistics

About this title

Synopsis

Explore nonparametric ways to compare dispersion patterns across multiple groups.

This book offers rank‑order approaches to testing homogeneity of dispersion matrices in multivariate data, focusing on procedures that are robust to outliers and do not rely on normality assumptions.

This edition develops a class of regular functionals and their rank‑based tests, including permutation methods and nonparametric alternatives. It explains how to handle both location and dispersion, discusses theoretical properties, and shows how to apply these tests to real‑world multivariate samples.

• Introduces generalized grades and dispersion matrices that stay informative under transformations
• Derives permutation‑based test statistics and their asymptotic behavior
• Compares nonparametric tests with classical parametric criteria and likelihood methods
• Offers practical guidance for implementing tests across multiple samples and dimensions

Ideal for researchers and practitioners in statistics who work with multivariate data and seek robust, distribution‑free ways to assess whether groups share the same spread and association structure.

Ideal for readers who want to deepen their understanding of nonparametric multivariate testing and its applications in data analysis.