A class of Bivariate SURE estimators in heteroscedastic hierarchical normal models
نویسندگان
چکیده
منابع مشابه
SURE Estimates for a Heteroscedastic Hierarchical Model.
Hierarchical models are extensively studied and widely used in statistics and many other scientific areas. They provide an effective tool for combining information from similar resources and achieving partial pooling of inference. Since the seminal work by James and Stein (1961) and Stein (1962), shrinkage estimation has become one major focus for hierarchical models. For the homoscedastic norm...
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Empirical Bayes approach is an attractive method for estimating hyperparameters in hierarchical models. But, under the assumption of normality for a multi-level heteroscedastic hierarchical model, which involves several explanatory variables, the analyst may often wonder whether the shrinkage estimators have efficient asymptotic properties in spite of the fact they involve numerous hyperparamet...
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Hierarchical models are powerful statistical tools widely used in scientific and engineering applications. The homoscedastic (equal variance) case has been extensively studied, and it is well known that shrinkage estimates, the James-Stein estimate in particular, offer nice theoretical (e.g., risk) properties. The heteroscedastic (the unequal variance) case, on the other hand, has received less...
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ژورنال
عنوان ژورنال: Journal of Statistical Theory and Applications
سال: 2018
ISSN: 1538-7887
DOI: 10.2991/jsta.2018.17.2.11