Measures of Dependence for Evaluating Information in Censored Models.

Abstract

Measures of information in censored models are developed by adapting measures of dependence between the lifetime variable and the observed variable. Some common notions of bivariate dependence and coefficients of divergence are used to derive these classes of measures. It is shown that most of the measures of bivariate dependence have the fundamental property that as censoring decreases stochastically, the information increases. An exception occurs when dependence is defined in terms of association. Conditions under which the coefficients of divergence enjoy the fundamental property are established. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1985
Accession Number
ADA170691

Entities

People

  • Frank Proschan
  • James Sconing
  • Myles Hollander

Organizations

  • Florida State University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Coefficients
  • Data Processing
  • Data Science
  • Information Science
  • Information Theory
  • New York
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Quadrants
  • Random Variables
  • Scientific Research
  • Statistics
  • Theorems
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Statistical inference.