首页> 外文期刊>Statistical Papers >Comparisons of the r ? k class estimator to the ordinary least squares estimator under the Pitman’s closeness criterion
【24h】

Comparisons of the r ? k class estimator to the ordinary least squares estimator under the Pitman’s closeness criterion

机译:r的比较Pitman贴近度准则下的k类估计量到普通最小二乘估计量

获取原文
获取原文并翻译 | 示例
           

摘要

In the presence of multicollinearity, the r − k class estimator is proposed as an alternative to the ordinary least squares (OLS) estimator which is a general estimator including the ordinary ridge regression (ORR), the principal components regression (PCR) and the OLS estimators. Comparison of competing estimators of a parameter in the sense of mean square error (MSE) criterion is of central interest. An alternative criterion to the MSE criterion is the Pitman’s (1937) closeness (PC) criterion. In this paper, we compare the r − k class estimator to the OLS estimator in terms of PC criterion so that we can get the comparison of the ORR estimator to the OLS estimator under the PC criterion which was done by Mason et al. (1990) and also the comparison of the PCR estimator to the OLS estimator by means of the PC criterion which was done by Lin and Wei (2002).
机译:在存在多重共线性的情况下,建议使用r-k类估计器来替代普通最小二乘(OLS)估计器,该估计器是包括普通岭回归(ORR),主成分回归(PCR)和OLS的常规估计器估计量。在均方误差(MSE)准则的意义上比较参数的竞争估计量非常重要。 MSE准则的替代准则是Pitman(1937)接近度(PC)准则。在本文中,我们根据PC准则将r-k类估计量与OLS估计量进行了比较,从而可以在由Mason等人完成的PC准则下获得ORR估计量与OLS估计量的比较。 (1990年),以及通过PC准则将PCR估计量与OLS估计量进行比较,这是由Lin和Wei(2002)完成的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号