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- W2110295031 abstract "We consider the problem of estimating the mean vector of a multivariate normal distribution under a variety of assumed structures among the parameters of the sampling and prior distributions. We adopt a pragmatic approach. We adopt distributional familites, assess hyperparmeters, and adopt patterned mean and coveariance structures when it is relatively simple to do so; alternatively, we use the sample data to estimate hyperparameters of prior distributions when assessment is a formidable task; such as the task of assessing parameters of multidimensional problems. James-Stein-like estimators are found to result. In some cases, we've been abl to show that the estimators proposed uniformly dominate the MLE's when measured with respect to quadratic loss functions." @default.
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- W2110295031 date "1986-01-01" @default.
- W2110295031 modified "2023-10-16" @default.
- W2110295031 title "Empirical bayes estimation of the mean in a multivariate normal distribution" @default.
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- W2110295031 doi "https://doi.org/10.1080/03610928608829244" @default.
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