贝塔回归模型的改进型刘岭估计值

IF 1.1 4区数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Statistical Computation and Simulation Pub Date : 2024-09-11 DOI:10.1080/00949655.2024.2396001

Mahmoud A. Abdel-Fattah

引用次数: 0

摘要

本文的主要目的是为无条件贝塔回归模型引入一类新的估计器。这一类新估计器被命名为刘岭型（LRT），其中包含两个收缩参数。

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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Improved Liu-ridge-type estimates for the beta regression model

The main objective of this paper is to introduce a new class of estimators for the ill-conditioned beta regression model. The new class, named the Liu-ridge-type (LRT), incorporates two shrinkage p...

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来源期刊

Journal of Statistical Computation and Simulation 数学-计算机：跨学科应用

CiteScore

2.30

自引率

8.30%

发文量

156

审稿时长

4-8 weeks

期刊介绍： Journal of Statistical Computation and Simulation ( JSCS ) publishes significant and original work in areas of statistics which are related to or dependent upon the computer. Fields covered include computer algorithms related to probability or statistics, studies in statistical inference by means of simulation techniques, and implementation of interactive statistical systems. JSCS does not consider applications of statistics to other fields, except as illustrations of the use of the original statistics presented. Accepted papers should ideally appeal to a wide audience of statisticians and provoke real applications of theoretical constructions.