Sensitivity of Bayes Inference with Ignorable but Data-Dependent Stopping Rules.

Abstract

It is sometimes argued that Bayesian inference is unaffected by data dependent stopping rules. Although this is formally true for ignorable rules, there is likely to be heightened sensitivity of inference to prior assumptions when using data dependent rules rather than stopping rules that do not depend on the data. This point is illustrated in a simple example. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1982
Accession Number
ADA125306

Entities

People

  • Donald B. Rubin
  • Paul R. Rosenbaum

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Bayesian Inference
  • Data Science
  • Frequency
  • Information Science
  • Intervals
  • Mathematics
  • Neoplasms
  • Probability
  • Sensitivity
  • Specifications
  • Standards
  • Statistics
  • Surveys
  • Theorems
  • United States
  • Universities
  • Wisconsin

Fields of Study

  • Computer science
  • Psychology

Readers

  • Neural Network Machine Learning.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Translation