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负相协样本分布函数的递归型核估计

A Recursive Distribution Function Estimator Under NA Samples
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摘要 设{Xn;n≥1}是一实值平稳负相协具有相同未知分布函数F(x)的随机变量序列,本文给出了F(x)一种递归型核估计F∧n(x)=1nj∑=n1K(x-hjXj),并讨论了它的渐近正态性,这里K(.)是已知的分布函数,窗宽{hj}满足hj↓0(j→+∞)。 Let{ Xn; n≥ 1 } be a strictly stationary sequence, and satisfying the basic requirement of being negatively asso-ciated, let F(x) be the marginal distribution function of {Xn}, which is estimated by the recursive kerneltype estimate ^∧Fn(x)=1/n∑^nj=n1K(x-Xj/hj) , Where bandwidthshj↓0 as j→+∞, kernel function K(·)is a known distribution function. In tiffs paper, we discuss the point asymptotic normality for ^∧Fn(x) under certain regularity conditions.
作者 李永明
机构地区 上饶师范学院
出处 《上饶师范学院学报》 2009年第6期6-10,25,共6页 Journal of Shangrao Normal University
基金 江西省自然科学基金(2008GZS0046) 江西省教育厅科技项目(GJJ09375)
关键词 负相协样本 递归估计 渐近正态性 Negative association reeursive estimate asymptotic normality
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参考文献14

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