Simultaneous Testing and Estimation with Dependent Chi-square Random Variables.

Abstract

Frequently the experimenter is confronted with an analysis involving two or more Chi-square random variables. This is often the case, for example, in experimental design or regression problems. Provided the Chi-square random variables are independent, probabilities associated with the random variable are easily determined. If the Chi-square random variables are not independent the analyses are much more complex and few practical tools are currently available to the experimenter. In the report the case of two dependent Chi-square random variables is discussed. A unified approach to solving the distributional problems is presented using canonical analysis. Density functions are derived for the bivariate Chi-square random variable with a special type of dependence. From a study of moments of the distribution, an approximation for any type of dependence using the special form mentioned above is suggested. (Author)

Document Details

Document Type
Technical Report
Publication Date
Mar 17, 1972
Accession Number
AD0745378

Entities

People

  • Richard F. Gunst

Organizations

  • Southern Methodist University

Tags

DTIC Thesaurus Topics

  • Data Science
  • Experimental Design
  • Information Science
  • Mathematics
  • Probability
  • Probability Distributions
  • Random Variables
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Statistical inference.
  • Systems Analysis and Design