generalized additive model

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Generalizations of Generalized Additive Model (GAM): A Case of Credit Risk Modeling

Famous for its easy implementation, Logistic Regression has been the primary model in credit scoring. Albeit attractively simple, it is criticized for failing to capture nonlinearity and nonmonotonicity and therefore possibly not leads to satisfactory results. Introduced by Hastie and Tibshirani, Generalized Additive Model GAM provides the ability to detect...

Tags: Credit Risk, Generalized Additive Model, Research & Development, Business Operations

White papers 2009-03-19

Additional Resources

Fitting Generalized Additive Models With the GAM Procedure in SAS 9.2

Generalized additive models are useful in finding predictor-response relationships in many kinds of data without using a specific model. They combine the ability to explore many nonparametric relationships simultaneously with the distributional flexibility of generalized linear models. The approach often brings to light nonlinear dependency structures in one's data. This...

Tags: SAS Institute

White papers 2008-03-13

Improving Credit Scoring by Generalized Additive Model

Logistic Regression has been widely used in the financial service industry for credit scoring models. Despite its advantages in easy interpretation and low computing cost, Logistic Regression is under the criticism of failure to model the nonlinear features of the predictor's effect on the dependent variable and therefore might lead...

Tags: Business Operations, Logistic Regression, Research & Development, SAS Institute

White papers 2007-05-14