Multivariate linear rank statistics for profile analysis

Vernon M. Chinchilli, Pranab Kumar Sen

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

For some general multivariate linear models, linear rank statistics are used in conjunction with Roy's Union-Intersection Principle to develop some tests for inference on the parameter (vector) when they are subject to certain linear constraints. More powerful tests are designed by incorporating the a priori information on these constraints. Profile analysis is an important application of this type of hypothesis testing problem; it consists of a set of hypothesis testing problem for the p responses q-sample model, where it is a priori assumed that the response-sample interactions are null.

Original languageEnglish (US)
Pages (from-to)219-229
Number of pages11
JournalJournal of Multivariate Analysis
Volume12
Issue number2
DOIs
StatePublished - Jun 1982

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

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