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ROC Function Estimation
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 Title & Authors
ROC Function Estimation
Hong, Chong-Sun; Lin, Mei Hua; Hong, Sun-Woo;
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 Abstract
From the point view of credit evaluation whose population is divided into the default and non-default state, two methods are considered to estimate conditional distribution functions: one is to estimate under the assumption that the data is followed the mixture normal distribution and the other is to use the kernel density estimation. The parameters of normal mixture are estimated using the EM algorithm. For the kernel density estimation, five kinds of well known kernel functions and four kinds of the bandwidths are explored. In addition, the corresponding ROC functions are obtained based on the estimated distribution functions. The goodness-of-fit of the estimated distribution functions are discussed and the performance of the ROC functions are compared. In this work, it is found that the kernel distribution functions shows better fit, and the ROC function obtained under the assumption of normal mixture shows better performance.
 Keywords
Bandwidth;density estimation;goodness-of-fit;normal mixture;kernel;performance;ROC function;
 Language
Korean
 Cited by
1.
대안적인 분류기준: 오분류율곱,홍종선;김효민;김동규;

응용통계연구, 2014. vol.27. 5, pp.773-786 crossref(new window)
1.
Alternative Optimal Threshold Criteria: MFR, Korean Journal of Applied Statistics, 2014, 27, 5, 773  crossref(new windwow)
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