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Mixture cure models in credit scoring: If and when borrowers default

Tong, Edward N.C.; Mues, Christophe; Thomas, Lyn C. - In: European Journal of Operational Research 218 (2012) 1, pp. 132-139

Mixture cure models were originally proposed in medical statistics to model long-term survival of cancer patients in terms of two distinct subpopulations – those that are cured of the event of interest and will never relapse, along with those that are uncured and are susceptible to the event....

Persistent link: https://www.econbiz.de/10010577544

Exposure at default models with and without the credit conversion factor

Tong, Edward N. C.; Mues, Christophe; Brown, Iain; … - In: European journal of operational research : EJOR 252 (2016) 3, pp. 910-920

Persistent link: https://www.econbiz.de/10011472989

Modelling credit card exposure at default using vine copula quantile regression

Wattanawongwan, Suttisak; Mues, Christophe; Okhrati, Ramin - In: European journal of operational research : EJOR 311 (2023) 1, pp. 387-399

Persistent link: https://www.econbiz.de/10014336533

A mixture model for credit card exposure at default using the GAMLSS framework

Wattanawongwan, Suttisak; Mues, Christophe; Okhrati, Ramin - In: International journal of forecasting 39 (2023) 1, pp. 503-518

Persistent link: https://www.econbiz.de/10014462794

The value of text for small business default prediction : a deep learning approach

Stevenson, Matthew; Mues, Christophe; Bravo, Cristián - In: European journal of operational research : EJOR 295 (2021) 2, pp. 758-771

Persistent link: https://www.econbiz.de/10013206023