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mgcv (version 1.3-11)

GAMs with GCV smoothness estimation and GAMMs by REML/PQL

Description

Routines for GAMs and other generalized ridge regression with multiple smoothing parameter selection by GCV or UBRE. Also GAMMs by REML or PQL. Includes a gam() function.

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Version

Install

install.packages('mgcv')

Monthly Downloads

106,646

Version

1.3-11

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

November 7th, 2025

Functions in mgcv (1.3-11)

anova.gam

Hypothesis tests related to GAM fits
magic.post.proc

Auxilliary information from magic fit
Predict.matrix

Prediction methods for smooth terms in a GAM
gam.check

Some diagnostics for a fitted gam model
extract.lme.cov

Extract the data covariance matrix from an lme object
gam.models

Specifying generalized additive models
smoothCon

Prediction/Construction wrapper functions for GAM smooth terms
formXtViX

Form component of GAMM covariance matrix
place.knots

Automatically place a set of knots evenly through covariate values
new.name

Obtain a name for a new variable that is not already in use
gam.control

Setting GAM fitting defaults
influence.gam

Extract the diagonal of the influence/hat matrix for a GAM
exclude.too.far

Exclude prediction grid points too far from data
magic

Stable Multiple Smoothing Parameter Estimation by GCV or UBRE, with optional fixed penalty
gamm.setup

Generalized additive mixed model set up
predict.gam

Prediction from fitted GAM model
gam.convergence

GAM convergence and performance issues
summary.gam

Summary for a GAM fit
notExp

Functions for better-than-log positive parameterization
full.score

GCV/UBRE score for use within nlm
pcls

Penalized Constrained Least Squares Fitting
vcov.gam

Extract parameter (estimator) covariance matrix from GAM fit
gam.setup

Generalized additive model set up
gam2objective

Objective functions for GAM smoothing parameter estimation
plot.gam

Default GAM plotting
null.space.dimension

The basis of the space of un-penalized functions for a TPRS
gam.fit

GAM P-IRLS estimation with GCV/UBRE smoothness estimation
mgcv-package

GAMs with GCV smoothness estimation and GAMMs by REML/PQL
pdIdnot

Overflow proof pdMat class for multiples of the identity matrix
vis.gam

Visualization of GAM objects
gamm

Generalized Additive Mixed Models
gam.selection

Generalized Additive Model Selection
s

Defining smooths in GAM formulae
te

Define tensor product smooths in GAM formulae
uniquecombs

find the unique rows in a matrix
gam.outer

Minimize GCV or UBRE score of a GAM using `outer' iteration
logLik.gam

Extract the log likelihood for a fitted GAM
gam.fit2

P-IRLS GAM estimation with GCV & UBRE derivative calculation
gam.neg.bin

GAMs with the negative binomial distribution
mroot

Smallest square root of matrix
pdTens

Functions implementing a pdMat class for tensor product smooths
gam.method

Setting GAM fitting method
fix.family.link

Modify families for use in GAM fitting
interpret.gam

Interpret a GAM formula
mgcv.control

Setting mgcv defaults
get.var

Get named variable or evaluate expression from list or data.frame
initial.sp

Starting values for multiple smoothing parameter estimation
mono.con

Monotonicity constraints for a cubic regression spline
residuals.gam

Generalized Additive Model residuals
notExp2

Alternative to log parameterization for variance components
smooth.construct

Constructor functions for smooth terms in a GAM
tensor.prod.model.matrix

Utility functions for constructing tensor product smooths
gamObject

Fitted gam object
fixDependence

Detect linear dependencies of one matrix on another
print.gam

Generalized Additive Model default print statement
gam

Generalized additive models with integrated smoothness estimation
formula.gam

Extract the formula from a gam object
mgcv

Multiple Smoothing Parameter Estimation by GCV or UBRE
gam.side

Identifiability side conditions for a GAM
step.gam

Alternatives to step.gam