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A lower bound for the Mismatched Maximum Likelihood estimator

机译:最大似然估计不匹配的下限

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A lower bound on Mean Square Error (MSE) of the estimate of a real deterministic parameter vector under misspecified model is proposed in this paper. In particular, a lower bound on the MSE of the Mismatched Maximum Likelihood (MML) estimator is derived in closed form and its relation with the Huber limit is investigated. Two simple illustrative examples are provided. Finally, the proposed framework is applied to the estimation of the scatter matrix in the Complex Elliptically Symmetric (CES) distribution family.
机译:提出了在错误指定的模型下,实际确定性参数矢量的估计值的均方误差(MSE)的下限。特别是,以封闭形式导出了不匹配最大似然(MML)估计量的MSE的下限,并研究了其与Huber极限的关系。提供了两个简单的说明性示例。最后,将所提出的框架应用于估计复杂椭圆对称(CES)分布族中的散射矩阵。

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