Analyzing credit risk data: A comparison of logistic discrimination, classification tree analysis, and feedforward networks

Computational Statistics

Volumn 12, Issue 2, 1997, Pages 293-310

  Arminger, Gerhard ^a   Enache, Daniel ^a   Bonne, Thorsten ^a  

^a UNIVERSITY OF WUPPERTAL   (Germany)

Author keywords

Artificial Neural Networks; Classification Trees; Combined Prediction; Logistic Discrimination

Indexed keywords

EID: 0031521799     PISSN: 09434062     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (14)

1. Arminger, G., (1993), Ökonometrische Schätzmethoden für neuronale Netze. In: Bol, G., Nakhaeizadeh, G., and Vollmer, K.-H. (eds): Finanzmarktanwendungen neuronaler Netze und ökonometrischer Verfahren, Physica Verlag, Heidelberg.
2. Arminger, G., and Enache, D., (1996), Statistical Models and Artificial Neural Networks. In: Bock, H. H., and Polasek, W. (eds.): Data Analysis and Information Systems. Statistical and Conceptual Approaches. Studies in Classification, Data Analysis, and Knowledge Organization, Vol. 7, Springer Verlag, Heidelberg, 243-260.
3. Breiman, L., Friedman, Jerome H., Olshen, Richard A., and Stone, C. J. (1984), Classification and Regression Trees, Wadsworth International Group, Belmont.
4. Cheng, B., and Titterington, D. M. , (1994), "Neural Networks: A Review from a Statistical Perspective", Statistical Science, 9, No. 1, 2-54.
5. Fahrmeir, L., Häußler, W., and Tutz, G. (1984), "Diskriminanzanalyse". In: Fahrmeir, L., and Hamerle, A. (eds.): Multivariate statistische Verfahren, de Gruyter, Berlin, 301-370.
6. Francis, B., Green, M., and Payne, C. (1993), The GLIM System, Release 4 Manual, Claredon Press, Oxford.
7. Hertz, J., Krogh, A, and Palmer, R. G., (1991), Introduction to the Theory of Neural Computation, Addison-Wesley, Redwood City, CA.
8. McLachlan, G. J. (1992), Discriminant Analysis and Statistical Pattern Recognition, Wiley, New York.
9. Ripley, B. D. (1993), "Statistical Aspects of Neural Networks". In: Barndorff, O. E., Jensen, J. L., and Kendall, W. S. (eds.): Networks and Chaos: Statistical and Probabilistic Aspects, Chapman&Hall, London, 40-123.
10. Sarle W. S., (1994), Neural Networks and Statistical Models. Proceedings of the Nineteenth Annual SAS Users Group International Conference, April, SAS Institute Inc., Cary, NC.
11. Steinberg, D., and Colla, P. (1995), CART: Tree-Structured Non-Parametric Data Analysis, Salford Systems, San Diego, CA.
12. Wernecke, K.-D., (1992), "A Coupling Procedure for the Discrimination of Mixed Data", Biometrics, 48, 497-506.
13. White, H., (1989a), Learning in Artificial Neural Networks: A Statistical Perspective, Neural Computation, 1, 425-464.
14. White, H., (1989b), "Some Asymptotic Results for Learning in Single Hidden-Layer Feedforward Network Models", Journal of the American Statistical Association, 84, No. 408, 1003-1013.