|
| << previous | next >> |
Journal description
All volumes of the corresponding journal
All issues of the corresponding volume
All articles of the corresponding issues
Details for article 3 of 19 found articles
| Title: |
Bayesian analysis of categorical data informatively censored |
| Author: |
Paulino, Carlos Daniel Mimoso Pereira, Carlos Alberto De Braganca |
| Appeared in: |
Communications in statistics |
| Paging: | Volume 21 (1992) nr. 9 pages 2689-2705 |
| Year: |
1992 |
| Contents: |
This article presents a general Bayesian analysis of incomplete categorical data considered as generated by a statistical model involving the categorical sampling process and the observable censoring process. The novelty is that we allow dependence of the censoring process paramenters on the sampling categories; i.e., an informative censoring process. In this way, we relax the assumptions under which both classical and Bayesian solutions have been de-veloped. The proposed solution is outlined for the relevant case of the censoring pattern based on partitions. It is completely developed for a simple but typical examples. Several possible extensions of our procedure are discussed in the final remarks. |
| Publisher: |
Taylor & Francis |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 3 of 19 found articles
| << previous | next >> |