⚠️There's a newer version (1.9-3) of this package.Take me there.

mgcv (version 0.6-2)

Multiple smoothing parameter estimation and GAMs by GCV

Description

Routines for GAMs and other generalized ridge regression problems with multiple smoothing parameter selection by GCV or UBRE. Includes an implementation (not a clone) of gam().

Copy Link

Version

Install

install.packages('mgcv')

Monthly Downloads

481,715

Version

0.6-2

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

April 4th, 2025

Functions in mgcv (0.6-2)

gam.fit

Generalized Additive Models fitting using penalized regression splines and GCV

pcls

Penalized Constrained Least Squares Fitting

GAMsetup

Set up GAM using penalized cubic regression splines

uniquecombs

find the unique rows in a matrix

gam.control

Setting Generalized Additive Models fitting defaults

theta.maxl

Estimate theta of the Negative Binomial by Maximum Likelihood

residuals.gam

Generalized Additive Model residuals

get.family

Identifies families

predict.gam

Prediction from fitted GAM model

neg.bin

Family function for Negative Binomial GAMs

SANtest

Example of simple additive GAM using penalized regression splines.

mgcv

Multiple Smoothing Parameter Estimation by GCV or UBRE

print.gam

Generalized Additive Model default print statement

gam.setup

Generalized Additive Model set up.

gam.parser

Generalized Additive Model fitting using penalized regression splines and GCV

null.space.dimension

Dimension of the space of un-penalized functions.

Defining smooths in GAM formulae

QT factorisation of a matrix

persp.gam

Perspective Plot of GAM objects

gam

Generalized Additive Models using penalized regression splines and GCV

mono.con

Monotonicity constraints for a cubic regression spline.

plot.gam

Default GAM plotting

gam.nbut

Generalized Additive Models using Negative Binomial errors with unknown theta