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MAXIMUM LIKELIHOOD ESTIMATION IN LINEAR MODELS WITH EQUI-CORRELATED RANDOM ERRORS

机译:具有等相关随机误差的线性模型的最大似然估计

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摘要

Necessary and sufficient conditions for the existence of maximum likelihood estimators of unknown parameters in linear models with equi-correlated random errors are presented. The basic technique we use is that these models are, first, orthogonally transformed into linear models with two variances, and then the maximum likelihood estimation problem is solved in the environment of transformed models. Our results generalize a result of Arnold, S. F. (1981) [The theory of linear models and multivariate analysis. Wiley, New York]. In addition, we give necessary and sufficient conditions for the existence of restricted maximum likelihood estimators of the parameters. The results of Birkes, D. & Wulff, S. (2003) [Existence of maximum likelihood estimates in normal variance-components models. J Statist Plann. Inference. 113, 35-47] are compared with our results and differences are pointed out.
机译:给出了具有等相关随机误差的线性模型中未知参数的最大似然估计的存在的充要条件。我们使用的基本技术是,首先将这些模型正交转换为具有两个方差的线性模型,然后在转换后的模型环境中解决最大似然估计问题。我们的结果概括了Arnold,S. F.(1981)的结果[线性模型和多元分析的理论。纽约州威利]。此外,我们为参数的受限最大似然估计的存在提供了充要条件。 Birkes,D.&Wulff,S.(2003)的结果[在正常方差分量模型中最大似然估计的存在。 J统计学家计划。推理。 113,35-47]与我们的结果进行比较,并指出了差异。

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