Enhancing model predictions through the fusion of stein estimator and principal component regression

IF 1.1 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Statistical Computation and Simulation Pub Date : 2024-01-09 DOI:10.1080/00949655.2024.2302011
Rasha A. Farghali, Adewale F. Lukman, Ayodeji Ogunleye
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Abstract

This research aims to enhance model predictions by introducing a novel approach that combines the Stein estimator technique with principal component regression (PCR) within the linear regression co...
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通过融合斯坦估算器和主成分回归增强模型预测能力
这项研究旨在通过引入一种新方法,在线性回归中将斯坦因估计器技术与主成分回归(PCR)相结合,从而增强模型预测。
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来源期刊
Journal of Statistical Computation and Simulation
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.
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