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vagam (version 1.1)

Variational Approximations for Generalized Additive Models

Description

Fits generalized additive models (GAMs) using a variational approximations (VA) framework. In brief, the VA framework provides a fully or at least closed to fully tractable lower bound approximation to the marginal likelihood of a GAM when it is parameterized as a mixed model (using penalized splines, say). In doing so, the VA framework aims offers both the stability and natural inference tools available in the mixed model approach to GAMs, while achieving computation times comparable to that of using the penalized likelihood approach to GAMs. See Hui et al. (2018) .

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Version

Install

install.packages('vagam')

Monthly Downloads

135

Version

1.1

License

GPL-3

Maintainer

Shang H

Last Published

December 6th, 2019

Functions in vagam (1.1)

predict.vagam

Predictions from a fitted generalized additive model (GAM).
summary.vagam

Summary of generalized additive model (GAM) fitted using variational approximations (VA).
plot.vagam

Basic plots for a fitted generalized additive model (GAMs).
gamsim

Simulate example datasets from a generalized additive models (GAM).
vagam-package

Variational approximations for generalized additive models
vagam

Fitting generalized additive models (GAMs) using variational approximations (VA).
wage_data

Union membership data set