A note on almost unbiased generalized ridge regression estimator under asymmetric loss
A note on almost unbiased generalized ridge regression estimator under asymmetric loss
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DOI：
10.1080/00949659908811943
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发表时间：
1999-03-01
影响因子：
1.2
通讯作者：
Wan, ATK
中科院分区：
文献类型：
--
作者：
Wan, ATK
使用非对称LINEX损失函数，我们推导和数值计算几乎无偏可行广义岭回归估计的精确风险函数。与（有偏）可行广义岭估计的性质相反，发现几乎无偏可行广义岭估计不严格优于传统的最小二乘估计，且与损失不对称无关.我们的数值结果表明，在很宽的参数值范围内，几乎无偏可行广义岭估计劣于最小二乘或可行广义岭估计。
Using the asymmetric LINEX loss function, we derive and numerically evaluate the exact risk function of the almost unbiased feasible generalized ridge regression estimator. Contrary to the properties of the (biased) feasible generalized ridge estimator, it is found that regardless of the loss asymmetry, the almost unbiased feasible generalized ridge estimator does not strictly dominate the traditional least squares estimator. Our numerical results show that over a wide range of parameter values, the almost unbiased feasible generalized ridge estimator is inferior to either the least squares or the feasible generalized ridge estimators.