文章基本信息

标题：OneStep : Le Cam's One-step Estimation Procedure
本地全文：下载
作者：Alexandre Brouste ; Christophe Dutang ; Darel Noutsa Mieniedou 等
期刊名称：R News
印刷版ISSN：1609-3631
出版年度：2021
卷号：13
期号：1
页码：366-377
语种：English
出版社：The R Foundation for Statistical Computing
摘要：The OneStep package proposes principally an eponymic function that numerically computes Le Cam’s one-step estimator, which is asymptotically efficient and can be computed faster than the maximum likelihood estimator for large datasets. Monte Carlo simulations are carried out for several examples (discrete and continuous probability distributions) in order to exhibit the performance of Le Cam’s one-step estimation procedure in terms of efficiency and computational cost on observation samples of finite size.