Empirical Bayes test for the truncation parameter of skew distribution
Skew distribution is a kind of generalization of the symmetric distribution and is widely applied in real life,where the truncation parameter to define the boundary of the skew distribution is of great significance.In this study,the empirical Bayes test is discussed for the truncation parameter in the skew distribution.Considering the unpredictability and uncertainty of prior density function in the common Bayes test,the unknown prior density function is estimated by the recursive kernel density function.In order to better characterize the decision risk,the weighted linear loss function of the test is defined.The asymptotic optimality of the proposed test function is proved under given conditions,and the determined convergence rates is given.Finally,the theoretical results are verified by a real example.
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维普
