Mean Squared Error Properties of Empirical Bayes Estimators in a Multivariate Random Effects General Linear Model

1985 ◽  
Vol 80 (391) ◽  
pp. 642-650 ◽  
Author(s):  
Gregory C. Reinsel
Keyword(s):  
Linear Model ◽  
Random Effects ◽  
Empirical Bayes ◽  
Mean Squared Error ◽  
General Linear Model ◽  
General Linear ◽  
Bayes Estimators ◽  
Squared Error ◽  
Empirical Bayes Estimators

Data Processing and Technology Application in Bayes and Empirical Bayes Reliability Analysis of Parameter of Ailamujia Distribution

2014 ◽  
Vol 951 ◽  
pp. 249-252
Author(s):  
Hui Zhou
Keyword(s):  
Empirical Bayes ◽  
Bayes Estimators ◽  
Conjugate Prior ◽  
Likelihood Estimator ◽  
Empirical Bayesian ◽  
Technology Application ◽  
Inverse Gamma ◽  
Squared Error ◽  
Linex Loss ◽  
Empirical Bayes Estimators

The estimation of the parameter of the ЭРланга distribution is discussed based on complete samples. Bayes and empirical Bayesian estimators of the parameter of the ЭРланга distribution are obtained under squared error loss and LINEX loss by using conjugate prior inverse Gamma distribution. Finally, a Monte Carlo simulation example is used to compare the Bayes and empirical Bayes estimators with the maximum likelihood estimator.

Data Processing with Computation in Bayes Reliability Analysis for Burr Type X Distribution under Different Loss Functions

2014 ◽  
Vol 978 ◽  
pp. 205-208
Author(s):  
Hui Zhou
Keyword(s):  
Prior Distribution ◽  
Unknown Parameter ◽  
Empirical Bayes ◽  
Loss Functions ◽  
Bayes Estimators ◽  
Likelihood Estimator ◽  
Squared Error Loss ◽  
Squared Error ◽  
Linex Loss ◽  
Empirical Bayes Estimators

This paper studies the estimation of the parameter of Burr Type X distribution. Maximum likelihood estimator is first derived, and then the Bayes and Empirical Bayes estimators of the unknown parameter are obtained under three loss functions, which are squared error loss, LINEX loss and entropy loss functions. The prior distribution of parmeter used in this paper is Gamma distribution. Finally, a Monte Carlo simulation is given to illustrate the application of these estimators.

scholarly journals EMPIRICAL BAYES ESTIMATION OF COEFFICIENTS IN THE GENERAL LINEAR MODEL FROM DATA OF DEFICIENT RANK1

1982 ◽  
Vol 1982 (1) ◽  
pp. i-16
Author(s):  
Henry I. Braun ◽  
Douglas H. Jones ◽  
Donald B. Rubin ◽  
Dorothy T. Thayer
Keyword(s):  
Linear Model ◽  
Empirical Bayes ◽  
General Linear Model ◽  
Bayes Estimation ◽  
General Linear ◽  
Empirical Bayes Estimation

Empirical bayes estimation of coefficients in the general linear model from data of deficient rank

Psychometrika ◽  
1983 ◽  
Vol 48 (2) ◽  
pp. 171-181 ◽  
Author(s):  
Henry I. Braun ◽  
Douglas H. Jones ◽  
Donald B. Rubin ◽  
Dorothy T. Thayer
Keyword(s):  
Linear Model ◽  
Empirical Bayes ◽  
General Linear Model ◽  
Bayes Estimation ◽  
General Linear ◽  
Empirical Bayes Estimation

EEG-fMRI: Including sleep-induced potentials in the general linear model improves spatial accordance with epileptic focus

2010 ◽  
Vol 41 (02) ◽  
Author(s):  
J Möhring ◽  
D Coropceanu ◽  
F Möller ◽  
S Wolff ◽  
R Boor ◽  
...  
Keyword(s):  
Linear Model ◽  
General Linear Model ◽  
General Linear ◽  
Epileptic Focus
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