Credit Scoring Using Splines

被引：0
|
作者：
Koo, Ja-Yong [1 ]
Choi, Daewoo [2 ]
Choi, Min-Sung [3 ]
机构：
[1] Korea Univ, Dept Stat, Anam Dong 5-1, Seoul 136701, South Korea
[2] Hankuk Univ Foreign Studies, Dept Stat, Yongin 449791, Kyongki Do, South Korea
[3] Lotte Card, Credit Management Team, Seoul 135974, South Korea
来源：
KOREAN JOURNAL OF APPLIED STATISTICS | 2005年 / 18卷 / 03期
关键词：
Grouping; Basis function methodology; Linear spline; Credit risk; Discriminant analysis; Function estimation;
D O I：
暂无
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Linear logistic regression is one of the most widely used method for credit scoring in credit risk management. This paper deals with credit scoring using splines based on logistic regression. Linear splines and an automatic basis selection algorithm are adopted. The final model is an example of the generalized additive model. A simulation using a real data set is used to illustrate the performance of the spline method.
引用
收藏
页码：543 / 553
页数：11
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