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Shrinkage estimators for prediction out-of-sample: Conditional performance
James-Stein estimator rando mmatrix theory random design
2012/11/22
We find that, in a linear model, the James-Stein estimator, which dominates the maximum-likelihood estimator in terms of its in-sample prediction error, can perform poorly compared to the maximum-like...
Geometric sensitivity of random matrix results: consequences for shrinkage estimators of covariance and related statistical methods
random matrix related statistical shrinkage estimators
2011/6/16
Shrinkage estimators of covariance are an important tool in modern applied and theoretical statistics.
They play a key role in regularized estimation problems, such as ridge regression (aka Tykhonov
...
A Class of Shrinkage Estimators for Variance of a Normal Population
Shrinkage Estimators Variance a Normal Population
2009/9/17
A Class of Shrinkage Estimators for Variance of a Normal Population。