The Comparison Between Maximum Weighted and Trimmed Likelihood Estimator of the Simple Circular Regression Model

Q3 Mathematics

Journal of Modern Applied Statistical Methods Pub Date : 2020-07-24 DOI:10.22237/jmasm/1604188920

Ehab A. Mahmood, H. Midi, A. G. Hussin

引用次数: 0

Abstract

The Maximum Likelihood Estimator (MLE) was used to estimate unknown parameters of the simple circular regression model. However, it is very sensitive to outliers in data set. A robust method to estimate model parameters is proposed.

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简单圆回归模型的最大加权似然估计与修剪似然估计的比较

利用极大似然估计器(MLE)对简单循环回归模型的未知参数进行估计。然而，它对数据集中的异常值非常敏感。提出了一种鲁棒估计模型参数的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Modern Applied Statistical Methods STATISTICS & PROBABILITY-

CiteScore

0.50

自引率

0.00%

发文量

期刊介绍： The Journal of Modern Applied Statistical Methods is an independent, peer-reviewed, open access journal designed to provide an outlet for the scholarly works of applied nonparametric or parametric statisticians, data analysts, researchers, classical or modern psychometricians, and quantitative or qualitative methodologists/evaluators.