广义收缩估计的拟合优度

IF 0.4 Q4 STATISTICS & PROBABILITY Theory of Probability and Mathematical Statistics Pub Date : 2020-08-05 DOI:10.1090/tpms/1106
Chi-Lun Cheng, Shalabh, A. Chaturvedi
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引用次数: 2

摘要

本文发展了由收缩型估计器拟合的线性回归模型的拟合优度统计量。一类双k类估计量被认为是包含多个估计量作为其特殊情况的收缩估计量。在已知和未知两种情况下,假设误差项的协方差矩阵为非单位矩阵。基于多元线性回归模型中决定系数的思想,提出了双k类估计量族的拟合优度统计量。导出了它的一阶和二阶矩直至一阶近似,并利用蒙特卡罗模拟研究了有限样本性质。
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Goodness of fit for generalized shrinkage estimation
The present paper develops a goodness of fit statistic for the linear regression models fitted by the shrinkage type estimators. A family of double k-class estimators is considered as a shrinkage estimator which encompasses several estimators as its particular case. The covariance matrix of error term is assumed to be a non-identity matrix under two situationsknown and unknown. The goodness of fit statistics based on the idea of coefficient of determination in multiple linear regression model is proposed for the family of double k-class estimators. Its first and second order moments up to the first order of approximation are derived and finite sample properties are studied using the Monte-Carlo simulation.
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来源期刊
CiteScore
1.30
自引率
0.00%
发文量
22
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