二次损失下一般Gauss-Markov模型中可估函数的Minimax可容许性

The Minimax Adimissibility of the Linear Estimator in the Gauss-markov Model under the Quadratic Function

对一般Gauss-Markov模型在齐次线性估计类中研究了Minimax可容许性,得出了线性Minimax估计在齐次线性估计类中可容许性的充分必要条件,接着对二次损失函数作了一些修改,采用类似齐次线性估计类中Minimax可容许性的研究方法,在非齐次线性估计类中研究了Minimax可容许性,得出了线性Minimax估计在非齐次线性估计类中可容许性的充分必要条件。

The paper studied the minimax admissibility of the Gauss-Markov model in the class of the homogeneous linear estimator and gain the necessary and sufficient condition. And then we studied the minimax admissibility in the class of the no homogeneous linear estimator by modifying the quadratic loss function and adopting the solving manner of studying the admissibility in the linear class of homogenous and gain the necessary and sufficient condition. Thus we purely and synthetically studied the minimax admissibility in all class of the estimator.