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mgcv (version 0.6-1)

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().

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Version

Install

install.packages('mgcv')

Monthly Downloads

481,715

Version

0.6-1

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

April 4th, 2025

Functions in mgcv (0.6-1)

predict.gam

Prediction from fitted GAM model

gam.control

Setting Generalized Additive Models fitting defaults

gam

Generalized Additive Models using penalized regression splines and GCV

null.space.dimension

Dimension of the space of un-penalized functions.

Defining smooths in GAM formulae

plot.gam

Default GAM plotting

SANtest

Example of simple additive GAM using penalized regression splines.

QT factorisation of a matrix

pcls

Penalized Constrained Least Squares Fitting

residuals.gam

Generalized Additive Model residuals

uniquecombs

find the unique rows in a matrix

gam.fit

Generalized Additive Models fitting using penalized regression splines and GCV

get.family

Identifies families

GAMsetup

Set up GAM using penalized cubic regression splines

print.gam

Generalized Additive Model default print statement

gam.nbut

Generalized Additive Models using Negative Binomial errors with unknown theta

mono.con

Monotonicity constraints for a cubic regression spline.

mgcv

Multiple Smoothing Parameter Estimation by GCV or UBRE

neg.bin

Family function for Negative Binomial GAMs

theta.maxl

Estimate theta of the Negative Binomial by Maximum Likelihood

persp.gam

Perspective Plot of GAM objects

gam.parser

Generalized Additive Model fitting using penalized regression splines and GCV

gam.setup

Generalized Additive Model set up.