The EM Algorithm for Censored Data.

Abstract

Three methods for applying the expectation maximization algorithm to censored data are considered, the Buckley-James, a proposed simpler nonparametric method and a normal model for censored data. A new estimator for the variance of y in the Buckley-James model is proposed and simulations comparing the three methods are described. To illustrate the use of these methods they are applied to the Stanford heart transplant data. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1984
Accession Number
ADA148136

Entities

People

  • H. Schneider
  • L. Weissfeld

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Biostatistics
  • Censorship
  • Data Science
  • Distribution Functions
  • Equations
  • Estimators
  • Information Science
  • North Carolina
  • Observation
  • Scientific Research
  • Security
  • Simulations
  • Statistics
  • Transplants
  • Universities

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

  • Biotechnology