Convergence of Dirichlet Measures Arising in Context of Bayesian Analysis of Competing Risks Models

Victor H. Salinas-Torres, Carlos A. de Bragança Pereira and Ram C. Tiwari

Journal of Multivariate Analysis, 1997, vol. 62, issue 1, 24-35

Abstract: In this paper, we study the weak convergence of Dirichlet measures on the class constituted by vectors of subprobability measures such that the sum of its components is a probability measure on a complete separable metric space. This vectorial class of subprobabilities appears in the context of the competing risks theory and the Dirichlet measures are considered as a prior family in a Bayesian approach. The weak convergence results are derived and used to study the convergence of the Bayes estimators of certain parameters in competing risks models.

Keywords: Dirichlet; processes; weak; convergence; random; censored; model; Bayes; estimation (search for similar items in EconPapers)
Date: 1997
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047-259X(97)91679-1
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:62:y:1997:i:1:p:24-35

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().