Robustness of the multiple correlation coefficient when sampling from a mixture of two multivariate normal populations

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

The density of the multiple correlation coefficient is derived by direct integration when the sample covariance matrix has a linear non-central distribution. Using the density, we deduce the null and non-null distribution of the multiple correlation coefficient when sampling from a mixture of two multivariate normal populations with the same covariance matrix. We also compute actual significance levels of the test of the hypothesis Ho: P1.2.p-0 versus Ha:P1.2…p> 0, given the mixture model.

Original languageEnglish
Pages (from-to)1443-1457
Number of pages15
JournalCommunications in Statistics - Simulation and Computation
Volume19
Issue number4
DOIs
Publication statusPublished - Jan 1 1990

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modelling and Simulation

Fingerprint Dive into the research topics of 'Robustness of the multiple correlation coefficient when sampling from a mixture of two multivariate normal populations'. Together they form a unique fingerprint.

  • Cite this