SURE Estimates for a Heteroscedastic Hierarchical Model

• Published in: Journal of the American Statistical Association Vol. 107; no. 500; pp. 1465 - 1479
• Main Authors: Xie, Xianchao, Kou, S. C., Brown, Lawrence D.
• Format: Journal Article
• Language: English
• Published: United States Taylor & Francis Group 01.12.2012; Taylor & Francis Ltd
• Subjects: Asymptotic methods; Asymptotic optimality; Bayes estimators; Datasets; Estimating techniques; Estimation; Estimation methods; Estimators; Heteroscedasticity; Hierarchical scales; Maximum likelihood estimation; Oracles; Risk theory; RSS technology; Sample size; Sampling; Scientific method; Shrinkage; Shrinkage estimator; Statistical analysis; Statistical discrepancies; Statistical methods; Statistical models; Statistics; Stein's unbiased risk estimate (SURE); Theory and Methods; Unbiased estimators; asymptotic optimality; hierarchical model; shrinkage estimator; Stein’s unbiased risk estimate (SURE); Heteroscedasticity

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 )...