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http://dx.doi.org/10.5351/KJAS.2010.23.5.943

Optimal Thresholds from Non-Normal Mixture  

Hong, Chong-Sun (Department of Statistics, Sungkyunkwan University)
Joo, Jae-Seon (Statistics and Panel Center, Korean Women's Development Institute)
Publication Information
The Korean Journal of Applied Statistics / v.23, no.5, 2010 , pp. 943-953 More about this Journal
Abstract
From a mixture distribution of the score random variable for credit evaluation, there are many methods of estimating optimal thresholds. Most the research news is based on the assumption of normal distributions. In this paper, we extend non-normal distributions such as Weibull, Logistic and Gamma distributions to estimate an optimal threshold by using a hypotheses test method and other methods maximizing the total accuracy and the true rate. The type I and II errors are obtained and compared with their sums. Finally we discuss their e ciency and derive conclusions for non-normal distributions.
Keywords
Credit; default; discriminatory; evaluation; optimal threshold; total accuracy; true rate;
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Times Cited By KSCI : 2  (Citation Analysis)
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