文章基本信息

标题：Robust estimators for circular regression models
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作者：Shokrya Alshqaq ; Ali Abuzaid ; Abdullah Ahmadini 等
期刊名称：Journal of King Saud University - Science
印刷版ISSN：1018-3647
出版年度：2021
卷号：33
期号：7
页码：1-6
DOI：10.1016/j.jksus.2021.101576
语种：English
出版社：Elsevier
摘要：AbstractThe problem of robust estimation in circular regression models has not been studied well. This paper considers theJScircular regression model due to its interesting properties and its sensitivity for existence and detection of outliers. We extend the robust estimators such asM-estimation, least-trimmed squares (LTS), and least-median squares (LMS) estimators, which have been successfully used in the linear regression models, to theJScircular regression model.The robustness of the proposed estimators are studied through its influence function, and via simulation study. The results show that the proposed robust circularM-estimation is effective in estimating circular models' parameters in the presence of vertical outliers. However, circularLTSandLMSare highly robust estimators in case of circular leverage points. An application of the proposed robust circular estimators is illustrated using a real eye data set.
关键词：Circular regression;Robust estimation;Influential function;Outlier;Bounded-influence estimate