Optimal estimator under risk matrix in a seemingly unrelated regression model and its generalized least squares expression
Optimal estimator under risk matrix in a seemingly unrelated regression model and its generalized least squares expression
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DOI：
10.1007/s00362-021-01232-5
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发表时间：
2021-04
影响因子：
1.3
通讯作者：
S. Matsuura;H. Kurata
中科院分区：
文献类型：
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作者：
S. Matsuura;H. Kurata
误差项可能具有同期相关性的一组多元回归模型被称为看似不相关的回归模型。本文在看似不相关的回归模型中建立了风险矩阵下回归向量的最佳等变估计量。应该注意的是，关于风险矩阵的最佳估计量在广泛的二次损失函数下仍然是最佳的。还提出了我们的估计量的广义最小二乘表达式。
A set of multiple regression models whose error terms have possibly contemporaneous correlations is called a seemingly unrelated regression model. In this paper, a best equivariant estimator of the regression vector under risk matrix is established in a seemingly unrelated regression model. It should be noted that an estimator optimal with respect to risk matrix remains optimal under a broad range of quadratic loss functions. A generalized least squares expression of our estimator is also presented.