Shrinkage estimates for multi-level heteroscedastic hierarchical normal linear models
نویسندگان
چکیده
منابع مشابه
Shrinkage estimates for multi-level heteroscedastic hierarchical normal linear models
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...
متن کاملEmpirical estimates for various correlations in longitudinal-dynamic heteroscedastic hierarchical normal models
In this paper, we first define longitudinal-dynamic heteroscedastic hierarchical normal models. These models can be used to fit longitudinal data in which the dependency structure is constructed through a dynamic model rather than observations. We discuss different methods for estimating the hyper-parameters. Then the corresponding estimates for the hyper-parameter that causes the association...
متن کاملOptimal Shrinkage Estimation in Heteroscedastic Hierarchical Models
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...
متن کاملSURE 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...
متن کاملHeteroscedastic linear models for analysing process data
In this paper the guidelines for applying heteroscedastic linear models for analysing industrial process data is presented. Heteroscedastic linear models are considered as a good model family for the joint modelling of dispersion and mean. The model selection of heteroscedastic linear model is discussed considering the special features of industrial data. A procedure for dispersion model select...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Statistical Theory and Applications
سال: 2015
ISSN: 2214-1766
DOI: 10.2991/jsta.2015.14.2.8