Generalized Additive Models with Flexible Response Functions

Standard generalized additive models assume a response function, which induces an assumption on the shape of the distribution of the response. However, miss-specifying the response function results in biased estimates. Therefore in Spiegel et al. (2017) we propose to estimate the response function jointly with the covariate effects. This package provides the underlying functions to estimate these generalized additive models with flexible response functions. The estimation is based on an iterative algorithm. In the outer loop the response function is estimated, while in the inner loop the covariate effects are determined. For the response function a strictly monotone P-spline is used while the covariate effects are estimated based on a modified Fisher-Scoring algorithm. Overall the estimation relies on the 'mgcv'-package.


News

FlexGAM 0.7.0

  • This is the first release of the package to CRAN.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("FlexGAM")

0.7.0 by Elmar Spiegel, a year ago


Browse source code at https://github.com/cran/FlexGAM


Authors: Elmar Spiegel [aut, cre]


Documentation:   PDF Manual  


GPL-2 license


Imports graphics, MASS, Matrix, scam, splines, stats

Depends on mgcv


See at CRAN