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In this paper we present a widely applicable definition of the predictive likelihood based on estimators that are either sufficient or approximately sufficient. Under regularity conditions, this predictive likelihood is shown to equal the Bayes prediction density up to terms of order O p(n-1)....
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The method of Bayesian model selection for join point regression models is developed. Given a set of "K"&plus;1 join point models "M"<sub>0</sub>, "M"<sub>1</sub>, …, "M"<sub>" K"</sub> with 0, 1, …, "K" join points respec-tively, the posterior distributions of the parameters and competing models "M"<sub>"k"</sub> are computed...
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Zellner (1975), Chaloner and Brant (1988), and Chaloner (1991) used the posterior distributions of the realized errors to define outliers in a linear model. The same concept is used here to define outliers in a state-space model. An effective approach to compute the posterior probabilities of...
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A random sample size version of the central limit theorem is obtained for a general class of symmetric statistics based on uniform spacings. An important application to goodness of fit test for a Poisson process is discussed.
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In this article we discuss uniformly most powerful unbiased tests for testing exponentiality against a specific class of two-parameter exponential models with increasing failure rate. We show that the optimal test statistic for this problem admits an alternative representation in terms of a...
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