混合 Kibria-Lukman 估计量在线性回归模型中的应用。
On the mixed Kibria-Lukman estimator for the linear regression model.
机构信息
College of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing, China.
School of Mathematics and Big Data, Chongqing University of Arts and Sciences, Chongqing, China.
出版信息
Sci Rep. 2022 Jul 20;12(1):12430. doi: 10.1038/s41598-022-16689-z.
This paper considers a linear regression model with stochastic restrictions,we propose a new mixed Kibria-Lukman estimator by combining the mixed estimator and the Kibria-Lukman estimator.This new estimator is a general estimation, including OLS estimator, mixed estimator and Kibria-Lukman estimator as special cases. In addition, we discuss the advantages of the new estimator based on MSEM criterion, and illustrate the theoretical results through examples and simulation analysis.
本文考虑了一个具有随机约束的线性回归模型，我们通过结合混合估计量和 Kibria-Lukman 估计量，提出了一种新的混合 Kibria-Lukman 估计量。这个新的估计量是一个通用的估计量，包括 OLS 估计量、混合估计量和 Kibria-Lukman 估计量作为特例。此外，我们还基于 MSEM 准则讨论了新估计量的优点，并通过实例和模拟分析说明了理论结果。
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