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Fitting Generalized Additive Models With the GAM Procedure in SAS 9.2

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software engineering

Overview 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 paper discusses an example of fitting generalized additive models with the GAM procedure, which provides multiple types of smoothers with automatic selection of smoothing parameters. This paper uses the ODS Statistical Graphics to produce plots of integrated additive and smoothing components.

Further White Paper Details
Publisher	SAS Institute	File Format	PDF
Date Published	March 2008
Format	White Papers
Topics	Software Engineering, Data Mining - Analysis

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