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Bayes and empirical bayes estimation of the probability that z > x + y
Authors:Jyoti N. Zalkikar  Ram C. Tiwari  S. Rao Jammalamadaka
Affiliation:Statistics and Applied Probability Program , University of California , Santa Barbara, CA, 93106
Abstract:Let X, Y and Z be independent random variables with common unknown distribution F. Using the Dirichlet process prior for F and squared erro loss function, the Bayes and empirical Bayes estimators of the parameters λ(F). the probability that Z > X + Y, are derived. The limiting Bayes estimator of λ(F) under some conditions on the parameter of the process is shown to be asymptotically normal. The aysmptotic optimality of the empirical Bayes estimator of λ(F) is established. When X, Y and Z have support on the positive real line, these results are derived for randomly right censored data. This problem relates to testing whether than used discussed by Hollander and Proshcan (1972) and Chen, Hollander and Langberg (1983).
Keywords:Dirichlet process prior  Bayes and empirical Bayes estimation  asymptotic optimality  new better than used distribution
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