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Statistical inference for P(X<Y).

Wang Zhou1

  • 1Department of Statistics and Applied Probability, National University of Singapore, Singapore. stazw@nus.edu.sg

Statistics in Medicine
|February 21, 2007
PubMed
Summary
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This study estimates the probability P(X

Area of Science:

  • Statistics
  • Probability Theory

Background:

  • The stress-strength model, P(X
  • Accurate statistical inference is needed for independent continuous random variables.

Purpose of the Study:

  • To develop and assess statistical inference methods for the stress-strength parameter theta = P(X
  • To evaluate the finite-sample accuracy of confidence intervals using Edgeworth expansions and bootstrap approximations.

Main Methods:

  • Utilizing Edgeworth expansions for statistical inference.
  • Applying bootstrap approximations to Studentized Wilcoxon-Mann-Whitney statistics.
  • Conducting simulation studies to assess confidence interval accuracy.

Main Results:

Related Experiment Videos

  • The study provides a detailed assessment of confidence interval performance.
  • Edgeworth expansions and bootstrap methods offer viable approaches for inference.
  • Simulation results indicate the finite-sample accuracy of the proposed methods.

    • Conclusions:

    • The proposed statistical inference methods are effective for the stress-strength model.
    • The study demonstrates the utility of Edgeworth expansions and bootstrap approximations.
    • The findings are validated through both simulated and real-world data applications.