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自适应截尾均值的方差
Asymptotic variances for trimmed means as adaptive location estimators in the exponential power family of distributions were derived by Prescott (1978). It is shown that, when the behaviour of the adapting statistic is accounted for, the variances may change significantly from the asymptotic values. Continuously adapting statistics are shown to be less desirable when the sample size is small.
自适应截尾均值的方差
Asymptotic variances for trimmed means as adaptive location estimators in the exponential power family of distributions were derived by Prescott (1978). It is shown that, when the behaviour of the adapting statistic is accounted for, the variances may change significantly from the asymptotic values. Continuously adapting statistics are shown to be less desirable when the sample size is small.
Since Robbins (1956), a large literature has evolved treating the empirical Bayes formulation of a sequence of decision problems. In this paper we look at the formulation and the asymptotic optimality criterion as a classical iid problem and a consistency property. With this point of view and the finite state component problem, we evoke classical results on Bayes procedures to prove a complete class theorem and to establish the asymptotic optimality of Bayes empirical Bayes…