Title: An Akaike information criterion for multiple event mixture cure models
Authors: Dirick, Lore ×
Claeskens, Gerda
Baesens, Bart #
Issue Date: 2015
Publisher: Elsevier
Series Title: European Journal of Operational Research vol:24 pages:449-457
Abstract: We derive the proper form of the Akaike information criterion for variable selection for mixture cure models, which are often fit via the expectation-maximization
algorithm. Separate covariate sets may be used in the mixture components. The selection criteria are applicable to survival models for right-censored data with multiple competing risks and allow for the presence of an insusceptible group. The method is illustrated on credit loan data, with pre-payment and default as events
and maturity as the insusceptible case and is used in a simulation study.
ISSN: 0377-2217
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
Research Center for Management Informatics (LIRIS), Leuven
× corresponding author
# (joint) last author

Files in This Item:
File Description Status SizeFormat
DirickClaeskensBaesens.pdfAn Akaike information criterion for multiple event mixture cure models Accepted 128KbAdobe PDFView/Open


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science