EconPapers    
Economics at your fingertips  
 

Nonparametric predictive inference for competing risks

T A Maturi, P Coolen-Schrijner and F P A Coolen

Journal of Risk and Reliability, 2010, vol. 224, issue 1, 11-26

Abstract: In reliability, failure data often correspond to competing risks, where several failure modes can cause a unit to fail. This paper presents nonparametric predictive inference (NPI) for competing risks data, assuming that the different failure modes are independent. NPI is a statistical approach based on few assumptions, with inferences strongly based on data and with uncertainty quantified via lower and upper probabilities. The focus is on the lower and upper probabilities for the event that a future unit will fail due to a specific failure mode. The paper illustrates the effect of grouping different failure modes together, and some special cases and features are discussed. It is also shown that NPI can easily deal with competing risks data resulting from experiments with progressive censoring. Furthermore, new formulae are presented for the NPI lower and upper survival functions.

Keywords: competing risks; imprecise reliability; lower and upper probabilities; lower and upper survival functions; nonparametric predictive inference; progressive censoring; right-censored data (search for similar items in EconPapers)
Date: 2010
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1243/1748006XJRR263 (text/html)

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:sae:risrel:v:224:y:2010:i:1:p:11-26

DOI: 10.1243/1748006XJRR263

Access Statistics for this article

More articles in Journal of Risk and Reliability
Bibliographic data for series maintained by SAGE Publications ().

 
Page updated 2025-03-19
Handle: RePEc:sae:risrel:v:224:y:2010:i:1:p:11-26