Accession Number : ADA006154

Title :   Some Contributions to Multivariate Nonparametric Methods.

Descriptive Note : Final rept. 1 Jul 71-30 Jun 74,

Corporate Author : NORTH CAROLINA UNIV CHAPEL HILL DEPT OF BIOSTATISTICS

Personal Author(s) : Sen,P. K.

Report Date : NOV 1974

Pagination or Media Count : 32

Abstract : Invariance principles for empirical processes, functionals of empirical distributions as well as of rank statistics provide useful tools for sophisticated studies of the distribution theory of these statistics. These results are also useful in the developing area of nonparametric sequential analysis. A general account of these invariance principles (with especial emphasis on the contributions by the principal investigator) is given here and their roles in (multivariate) nonparametric methods is discussed. Nonparametric classification procedures, mainly, the ones developed by S. K. Chatterjee, are also considered here. Finally, for the classical multivariate analysis of variance problems, especially, in the context of the so called growth curve models, the robustness of parametric procedures in the Behrens-Fisher situation, as has been studied by S. R. Chakravorti, is presented.

Descriptors :   *Multivariate analysis, *Nonparametric statistics, Invariance, Sequential analysis, Random variables, Estimates

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE