Robust Bayesian Inference on Scale Parameters
We represent random vectors Z that take values in n-{0} as Z=RY, where R is a positive random variable and Y takes values in an (n-1)-dimensional space . By fixing the distribution of either R or Y, while imposing independence between them, different classes of distributions on n can be generated. As examples, the spherical, lq-spherical, [upsilon]-spherical and anisotropic classes can be interpreted in this unifying framework. We present a robust Bayesian analysis on a scale parameter in the pure scale model and in the regression model. In particular, we consider robustness of posterior inference on the scale parameter when the sampling distribution ranges over classes related to those mentioned above. Some links between Bayesian and sampling-theory results are also highlighted.
Year of publication: |
2001
|
---|---|
Authors: | Fernández, Carmen ; Osiewalski, Jacek ; Steel, Mark F. J. |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 77.2001, 1, p. 54-72
|
Publisher: |
Elsevier |
Keywords: | posterior distribution scale invariance scale model regression model |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Inference robustness in multivariate models with a scale parameter
Fernández, Carmen, (1995)
-
Inference robustness in multivariate models with a scale parameter
Fernández, Carmen, (1995)
-
Robust Bayesian inference on scale parameters
Fernández, Carmen, (1996)
- More ...