Bayes and Empirical Bayes Shrinkage Estimation of Regression Coefficients
โ Scribed by Fassil Nebebe and T. W. F. Stroud
- Book ID
- 115056791
- Publisher
- John Wiley and Sons
- Year
- 1986
- Tongue
- French
- Weight
- 717 KB
- Volume
- 14
- Category
- Article
- ISSN
- 0319-5724
- DOI
- 10.2307/3315184
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
The multivariate normal regression model, in which a vector y of responses is to be predicted by a vector x of explanatory variables, is considered. A hierarchical framework is used to express prior information on both x and y. An empirical Bayes estimator is developed which shrinks the maximum like
Suppose that the random variable X is distributed according to exponential families of distributions, conditional on the parameter 0. Assume that the parameter 0 has a (prior) distribution G. Because of the measurement error, we can only observe Y = X+e, where the measurement error e is independent