| 摘 要： | Consider the two-sided truncation distribution families written in the form f(x,θ)=w(θ_1, θ_2)·h(x)I_(θ_1,θ_2])(x)dx, where θ=(θ_1,θ_2). T(X)=(t_1(X), t_2(X))=(min(X_1, …, X_m), max(X_1, …, X_m)) is a sufficient statistic and we denote its marginal density by f(t)dμ~T. The prior distribution of θ belong to the famlly. In this paper, we have constructed the empirical Bayes (EB) estimator of θ, φ_n(t), by using the kernel estimation of f(t) and established its convergence rates. Under suitable conditions it is shown that the rates of convergenc of EB estimator are O(N~-((λ中-1)(k 1))/(2(k 2)k)), where the neural number k>1 and 1/2<λ<1-1/2k. Finally an example about this result is given.
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