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mgcv (version 1.3-9)

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

1.3-9

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

November 7th, 2025

Functions in mgcv (1.3-9)

gamm

Generalized Additive Mixed Models
initial.sp

Starting values for multiple smoothing parameter estimation
gam.control

Setting GAM fitting defaults
gamObject

Fitted gam object
Predict.matrix

Prediction methods for smooth terms in a GAM
formXtViX

Form component of GAMM covariance matrix
exclude.too.far

Exclude prediction grid points too far from data
mroot

Smallest square root of matrix
extract.lme.cov

Extract the data covariance matrix from an lme object
gamm.setup

Generalized additive mixed model set up
residuals.gam

Generalized Additive Model residuals
gam2objective

Objective functions for GAM smoothing parameter estimation
gam.fit

GAM P-IRLS estimation with GCV/UBRE smoothness estimation
notExp

Functions for better-than-log positive parameterization
pdIdnot

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

Extract the formula from a gam object
fixDependence

Detect linear dependencies of one matrix on another
gam.models

Specifying generalized additive models
gam.neg.bin

GAMs with the negative binomial distribution
print.gam

Generalized Additive Model default print statement
magic.post.proc

Auxilliary information from magic fit
gam.selection

Generalized Additive Model Selection
gam.side

Identifiability side conditions for a GAM
gam.check

Some diagnostics for a fitted gam model
logLik.gam

Extract the log likelihood for a fitted GAM
gam.fit2

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

Hypothesis tests related to GAM fits
interpret.gam

Interpret a GAM formula
magic

Stable Multiple Smoothing Parameter Estimation by GCV or UBRE, with optional fixed penalty
mgcv

Multiple Smoothing Parameter Estimation by GCV or UBRE
mono.con

Monotonicity constraints for a cubic regression spline
gam.convergence

GAM convergence and performance issues
null.space.dimension

The basis of the space of un-penalized functions for a TPRS
mgcv.control

Setting mgcv defaults
fix.family.link

Modify families for use in GAM fitting
place.knots

Automatically place a set of knots evenly through covariate values
pcls

Penalized Constrained Least Squares Fitting
plot.gam

Default GAM plotting
notExp2

Alternative to log parameterization for variance components
gam

Generalized additive models with integrated smoothness estimation
pdTens

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

Generalized additive model set up
get.var

Get named variable or evaluate expression from list or data.frame
gam.outer

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

Prediction from fitted GAM model
full.score

GCV/UBRE score for use within nlm
smooth.construct

Constructor functions for smooth terms in a GAM
smoothCon

Prediction/Construction wrapper functions for GAM smooth terms
s

Defining smooths in GAM formulae
new.name

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

Alternatives to step.gam
gam.method

Setting GAM fitting method
influence.gam

Extract the diagonal of the influence/hat matrix for a GAM
tensor.prod.model.matrix

Utility functions for constructing tensor product smooths
vis.gam

Visualization of GAM objects
vcov.gam

Extract parameter (estimator) covariance matrix from GAM fit
uniquecombs

find the unique rows in a matrix
summary.gam

Summary for a GAM fit
te

Define tensor product smooths in GAM formulae