文章基本信息

标题：Consistency of the φ-Divergence Based Change Point Estimator
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作者：Mwelu Susan ; Anthony G. Waititu ; Peter N. Mwita 等
期刊名称：Open Journal of Statistics
印刷版ISSN：2161-718X
电子版ISSN：2161-7198
出版年度：2020
卷号：10
期号：5
页码：832-849
DOI：10.4236/ojs.2020.105048
出版社：Scientific Research Publishing
摘要：This paper utilizes a change-point estimator based on the φ-divergence. Since we seek a near perfect translation to reality, then locations of parameter change within a finite set of data have to be accounted for since the assumption of stationary model is too restrictive especially for long time series. The estimator is shown to be consistent through asymptotic theory and finally proven through simulations. The estimator is applied to the generalized Pareto distribution to estimate changes in the scale and shape parameters.
关键词：Change Point;Consistency;φ-Divergence;Kullback-Leibler;Generalized Pareto Distribution