Generalized Bayes Minimax Estimators of a Multiple Regression Coefficient Vector with Three or More Predictors.
FLORIDA STATE UNIV TALLAHASSEE DEPT OF STATISTICS
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Consider a multiple regression problem in which the dependent variable and 3 or more independent variables have a joint normal distribution with unknown mean vector and covariance matrix. A family of minimax estimators based on the maximum likelihood estimator and the sample multiple correlation is obtained for the regression coefficient vector. It is shown that there are minimax estimators of the same form as the ones mentioned above, which are also generalized Bayes. The problem of estimating both the intercept and regression coefficient vector is also investigated. Author
- Statistics and Probability