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What is Understanding Generalized Additive Models about?
This document discusses generalized additive models (GAMs) as an improvement over generalized linear models (GLMs) for handling continuous variables. GAMs allow the modeling of continuous variables using non-parametric smoothers rather than categorization or transformations. This provides a more flexible and data-driven approach. The document provides examples of smoothers that can be used in GAMs and explains how GAMs are fit using backfitting to reduce dimensionality. It also provides sample SAS code for
- Author
- Reny Lase
- Language
- EN