Pregled bibliografske jedinice broj: 124089
Credit scoring using robust logistic regression
Credit scoring using robust logistic regression // Proceedings of 8th meeting of the Austrian, Croatian, Hungarian, Italian, Slovenian young statisticians / A. Ferligoj, H. Friedl, D. Gregori, T. Poganj, T. Rudas (ur.).
Veszprém: SKICC Reklamstudio Kft., 2003. str. 37-54 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Credit scoring using robust logistic regression
Autori
Bokun, Goran
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of 8th meeting of the Austrian, Croatian, Hungarian, Italian, Slovenian young statisticians
/ A. Ferligoj, H. Friedl, D. Gregori, T. Poganj, T. Rudas - Veszprém : SKICC Reklamstudio Kft., 2003, 37-54
Skup
8th Regional Meeting of Young Statisticians 2003 (Austria, Croatia, Hungary, Italy, Slovenia)
Mjesto i datum
Balatonföldvár, Mađarska, 17.10.2003. - 19.10.2003
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
credit scoring; robust method; logistic regression
Sažetak
The objective of this paper is to investigate the possibility of improving a predictive power of the credit scoring model using robust logistic regression instead of the classical one. The robust procedures are usually used for data sets containing outliers. As we deal with small business credits and a lot of non-financial variables, we cannot expect a data set without outliers. Some of the proposed robust procedures can be computationally very expensive. Our aim is to answer the question which robust procedure is to be used in order to get satisfactory predicting power and computational time.
Izvorni jezik
Engleski
Znanstvena područja
Matematika
