Parameter estimation based on cumulative Kullback-Leibler divergence

2016/06/29 by Yaser Mehrali, Mehrali, Yaser, Majid Asadi +1
Mathematics · #62B10 #62E20 #62F03 #62F05 #62F10 #62F12 #62F25 #62G30 #94A15 #94A17 #FOS: Mathematics #G.3 #Statistical Methods and Inference #Statistics Theory (math.ST) #acm:62B10 #acm:62E20 #acm:62F03 #acm:62F05 #acm:62F10 #acm:62F12 #acm:62F25 #acm:62G30 #acm:94A15 #acm:94A17 #math.ST #msc:62B10 #msc:62E20 #msc:62F03 #msc:62F05 #msc:62F10 #msc:62F12 #msc:62F25 #msc:62G30 #msc:94A15 #msc:94A17 #stat.TH

paper · pdf · doi:10.48550/arxiv.1606.09288

22 pages, 7 figures Presented in The 2nd Workshop on Information Measures and Their Applications Submitted to appear in Metrika

arxiv created 2016/06/29 · openalex publication_date 2016/06/29 · arxiv updated 2016/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, we propose some estimators for the parameters of a statistical model based on Kullback-Leibler divergence of the survival function in continuous setting. We prove that the proposed estimators are subclass of "generalized estimating equations" estimators. The asymptotic properties of the estimators such as consistency, asymptotic normality, asymptotic confidence interval and asymptotic hypothesis testing are investigated.

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