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| Titel: |
Bayesian analysis of categorical data informatively censored |
| Auteur: |
Paulino, Carlos Daniel Mimoso Pereira, Carlos Alberto De Braganca |
| Verschenen in: |
Communications in statistics |
| Paginering: | Jaargang 21 (1992) nr. 9 pagina's 2689-2705 |
| Jaar: |
1992 |
| Inhoud: |
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. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 3 van 19 gevonden artikelen
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