Stein estimation -- a review
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Publication:1567075
DOI10.1007/BF02926100zbMath1047.62506MaRDI QIDQ1567075
Publication date: 2000
Published in: Statistical Papers (Search for Journal in Brave)
Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Point estimation (62F10) Admissibility in statistical decision theory (62C15)
Related Items (10)
Asymptotically optimal shrinkage estimates for non-normal data ⋮ Bias Adjustment Minimizing the Asymptotic Mean Square Error ⋮ Confidence intervals for product of powers of the generalized variances of k multivariate normal populations ⋮ Bayesian regression based on principal components for high-dimensional data ⋮ Estimation of a subset of regression coefficients of interest in a model with non-spherical disturbances ⋮ Shrinkage estimation in spatial autoregressive model ⋮ Matrix shrinkage of high-dimensional expectation vectors ⋮ Stein-type estimation in logistic regression models based on minimum \(\phi\)-divergence estimators ⋮ Shrinkage-based similarity metric for cluster analysis of microarray data ⋮ Unimprovable solution to systems of empirical linear algebraic equations
Cites Work
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- Estimating the covariance matrix and the generalized variance under a symmetric loss
- Construction of improved estimators in multiparameter estimation for discrete exponential families
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- Improved confidence intervals for a normal variance
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- Dominating james-stein positive-part estimator for normal mean with unknown covariance matrix
- The exact risks of some pre-test and stein-type regression estimators umder balanced loss
- Adapting to Unknown Smoothness via Wavelet Shrinkage
- Optimal Confidence Intervals for the Variance of a Normal Distribution
- Robustness of Clevenson-Zidek-Type Estimators
- Further Developments on the Robustness of Clevenson-Zidek-Type Means Estimators
- Multiparameter estimation of discrete exponential distributions
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- Simultaneous Estimation of the Means of Independent Poisson Laws
- Double k-Class Estimators of Coefficients in Linear Regression
- Application of Pre-Test and Stein Estimators to Economic Data
- Compound poisson distributions: Properties and estimation*
- Risk Analysis and Robustness of four Shrinkage Estimators
- Estimators which are Uniformly Better than the James-Stein Estimator
- Preliminary-test estimation of the regression scale parameter when the loss function is asymmetric
- The neyman accuracy and the wolfowitz accuracy of the stein type confidence interval for the disturbance variance
- Stein type confidence interval of the disturbance variance in a linear regression model with multivariate student-t distributed errors
- An Empirical Bayes Stein-Type Estimator for Regression Parameters Under Linear Constraints
- Applications of Improved Variance Estimators in a Multivariate Normal Mean Vector Estimation
- Estimation Of A Multivariate Normal Mean Vector And Local Improvements
- Simultaneous Estimation of Poisson Means under Weighted Entropy Loss
- Improvements over the james-stein estimator: A risk analysis
- A Family of Minimax Estimators of the Mean of a Multivariate Normal Distribution
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