mgcv

Mixed GAM Computation Vehicle with Automatic Smoothness Estimation

Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) <doi:10.1201/9781315370279> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.

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Description file content

Package
mgcv
Version
1.8-27
Author
Simon Wood
Maintainer
Simon Wood
Title
Mixed GAM Computation Vehicle with Automatic Smoothness Estimation
Description
Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.
Priority
recommended
Depends
R (>= 2.14.0), nlme (>= 3.1-64)
Imports
methods, stats, graphics, Matrix, splines, utils
Suggests
parallel, survival, MASS
LazyLoad
yes
ByteCompile
yes
License
GPL (>= 2)
NeedsCompilation
yes
Packaged
2019-02-06 10:57:24 UTC; sw283
Repository
CRAN
Date/Publication
2019-02-06 15:00:03 UTC

install.packages('mgcv')

1.8-27

13 days ago

Simon Wood

GPL (>= 2)

Depends on

R (>= 2.14.0), nlme (>= 3.1-64)

Imports

methods, stats, graphics, Matrix, splines, utils

Suggests

parallel, survival, MASS

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