The neglog transformation and quantite regression for the analysis of a large credit scoring database

Journal of the Royal Statistical Society. Series C: Applied Statistics

Volumn 54, Issue 5, 2005, Pages 863-878

  Whittaker, Joe ^a,c   Whitehead, Chris ^a   Somers, Mark ^b  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b Scimetrics Ltd   (United Kingdom)

^c LANCASTER UNIVERSITY   (United Kingdom)

Author keywords

Collections; Large data sets; Missed payment database; Profit scoring; Training sample; Validation sample; Yeo Johnson power transformation

Indexed keywords

EID: 27344449456     PISSN: 00359254     EISSN: 14679876     Source Type: Journal    
DOI: 10.1111/j.1467-9876.2005.00520.x     Document Type: Article

References (8)

1. Box, G. E. P. and Cox, D. R. (1964) An analysis of transformations (with discussion). J. R. Statist. Soc. B, 26, 211-252.
2. Hastie, T., Tibshirani, R. and Friedman, J. (2001) The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer.
3. Koenker, R. and Bassett, G. W. (1978) Regression quantiles. Econometrica, 46, 33-50.
4. Koenker, R. and Hallock, K. (2001) Quantile regression. J. Econ. Perspect., 15, 143-156.
5. Koenker, R. and Machado, J. (1999) Goodness of fit and related inference processes for quantile regression. J. Am. Statist. Ass., 94, 1296-1310.
6. McNab, H. and Wynn, A. (2000) Principles and Practice of Consumer Credit Risk. Canterbury: Chartered Institute of Bankers.
7. Yeo, I. and Johnson, R. (2000) A new family of power transformations to improve normality or symmetry. Biometrika, 87, 954-959.
8. Yu, K., Lu, Z. and Stander, J. (2003) Quantile regression: applications and current research areas. Statistician, 52, 331-350.