An Algorithm for Clustered Data Generalized Additive Modelling with S-PLUS

Lin Yee Hin, Vincent Carey

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We present a set of functions in S-PLUS to implement the clustered data generalized additive marginal modelling (CDGAM) strategy proposed by Berhane and Tibshirani (1998). A variety of working correlation structures are supported, and the regression basis may include components from the family of smoothing splines.

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