• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of the Royal Statistical Society. Series C, Applied statistics >The neglog transformation and quantile regression for the analysis of a large credit scoring database
【24h】

The neglog transformation and quantile regression for the analysis of a large credit scoring database

机译：neglog变换和分位数回归，用于分析大型信用评分数据库

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A statistical analysis of a bank's credit card database is presented. The database is a snapshot of accounts whose holders have missed a payment on a given month but who do not subsequently default. The variables on which there is information are observable measures on the account (such as profit and activity), and whether actions that are available to the bank (such as letters and telephone calls) have been taken. A primary objective for the bank is to gain insight into the effect that collections activity has on on-going account usage. A neglog transformation that highlights features that are hidden on the original scale and improves the joint distribution of the covariates is introduced. Quantile regression, a novel methodology to the credit scoring industry, is used as it is relatively assumption free, and it is suspected that different relationships may be manifest in different parts of the response distribution. The large size is handled by selecting relatively small subsamples for training and then building empirical distributions from repeated samples for validation. In the application to the database of clients who have missed a single payment a substantive finding is that the predictor of the median of the target variable contains different variables from those of the predictor of the 30% quantile. This suggests that different mechanisms may be at play in different parts of the distribution.
机译：给出了银行信用卡数据库的统计分析。该数据库是帐户的快照，这些帐户的持有人在给定的月份内未付款，但随后没有拖欠付款。带有信息的变量是帐户上的可观察度量（例如利润和活动），以及是否已采取银行可用的操作（例如信件和电话）。银行的主要目标是深入了解收款活动对持续使用帐户的影响。引入了一个neglog变换，该变换突出显示隐藏在原始比例尺上的特征并改善了协变量的联合分布。使用分位数回归，这是一种针对信用评分行业的新颖方法，因为它相对没有假设，并且怀疑在响应分布的不同部分中可能表现出不同的关系。通过选择相对较小的子样本进行训练，然后从重复样本中建立经验分布进行验证，可以处理较大的样本。在错过一次付款的客户数据库的应用中，一个实质性发现是目标变量中位数的预测变量包含与30％分位数的预测变量不同的变量。这表明在分发的不同部分中可能发挥不同的作用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号