A Structure Theorem on Bivariate Positive Quadrant Dependent Distributions and Tests for Independence in Two-Way Contingency Tables.

Abstract

In this paper, the set of all bivariate positive quadrant dependent distributions with fixed marginals is shown to be compact and convex. Extreme points of this convex set are enumerated in some specific examples. Applications are given in testing the hypothesis of independence against strict positive quadrant dependence in the context of ordinal contingency tables. Various procedures based upon certain functions of the eigenvalues of a random matrix are also proposed for testing for independence in two-way contingency table. The performance of some tests one of which is based on eigenvalues of a random matrix is compared.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1985
Accession Number
ADA169968

Entities

People

  • K. Subramanyam
  • M. B. Rao
  • Paruchuri R. Krishnaiah

Organizations

  • University of Pittsburgh

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Classification
  • Convex Sets
  • Covariance
  • Data Science
  • Distribution Theory
  • Eigenvalues
  • Eigenvectors
  • Equations
  • Information Science
  • Multivariate Analysis
  • New York
  • Probability
  • Random Variables
  • Statistics
  • Theorems
  • Universities

Fields of Study

  • Mathematics

Readers

  • Graph Algorithms and Convex Optimization.
  • Regression Analysis.