Destructive weighted Poisson cure rate models with bivariate random effects: Classical and Bayesian approaches
Diego I. Gallardo,
Heleno Bolfarine and
Antonio Carlos Pedroso-de-Lima
Computational Statistics & Data Analysis, 2016, vol. 98, issue C, 31-45
Abstract:
In this paper, random effects are included in the destructive weighted Poisson cure rate model. For parameter estimation we implemented a classical approach based on the restricted maximum likelihood (REML) methodology and a Bayesian approach based on Dirichlet process priors. A small scale simulation study is conducted to discuss parameter recovery and the performance of the proposed methodology is illustrated with a real data example.
Keywords: REML; Dirichlet process; Competing risks (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S016794731500314X
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:csdana:v:98:y:2016:i:c:p:31-45
DOI: 10.1016/j.csda.2015.12.006
Access Statistics for this article
Computational Statistics & Data Analysis is currently edited by S.P. Azen
More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().