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pro vyhledávání: '"Lore Dirick"'
The specific nature of credit loan data requires the use of mixture cure models within the class of survival analysis tools. The constructed models allow for com-peting risks such as early repayment and default, and for incorporating maturity, expres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a9cf140e3e4a710713913a62946352b
https://lirias.kuleuven.be/handle/123456789/665249
https://lirias.kuleuven.be/handle/123456789/665249
Publikováno v:
Journal of the Operational Research Society. 68:652-665
We investigate the performance of various survival analysis techniques applied to ten actual credit data sets from Belgian and UK financial institutions. In the comparison we consider classical survival analysis techniques, namely the accelerated fai
The prediction of the time of default in a credit risk setting via survival analysis needs to take a high censoring rate into account. This rate is due to the fact that default does not occur for the majority of debtors. Mixture cure models allow the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39a11a46306642c1a821fd8a59f6bcf7
http://hdl.handle.net/10044/1/43470
http://hdl.handle.net/10044/1/43470
Publikováno v:
SSRN Electronic Journal.
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