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mgcv (version 1.3-0)

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

1.3-0

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

November 7th, 2025

Functions in mgcv (1.3-0)

Multiple Smoothing Parameter Estimation by GCV or UBRE

extract.lme.cov

Extract the data covariance matrix from an lme object

fix.family.link

Modify families for use in GAM fitting

GAMs with the negative binomial distribution

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

Setting GAM fitting defaults

Monotonicity constraints for a cubic regression spline.

Penalized Constrained Least Squares Fitting

Summary for a GAM fit

Visualization of GAM objects

GCV/UBRE score for use within nlm

Setting mgcv defaults

Automatically place a set of knots evenly through covariate values

Generalized additive models with integrated smoothness estimation

Identifiability side conditions for a GAM.

Fitted gam object

Hypothesis tests related to GAM fits

Functions implementing a pdMat class for tensor product smooths

Generalized Additive Model residuals

Starting values for multiple smoothing parameter estimation.

exclude.too.far

Exclude prediction grid points too far from data

Form component of GAMM covariance matrix

Extract the formula from a gam object.

magic.post.proc

Auxilliary information from magic fit

Setting GAM fitting method

Extract parameter (estimator) covariance matrix from GAM fit

Prediction from fitted GAM model

Generalized Additive Model set up.

Prediction methods for smooth terms in a GAM

tensor.prod.model.matrix

Utility functions for constructing tensor product smooths

Generalized Additive Mixed Models

Detect linear dependencies of one matrix on another

find the unique rows in a matrix

P-IRLS GAM estimation with GCV & UBRE derivative calculation

null.space.dimension

The basis of the space of un-penalized functions for a t.p.r.s.

Interpret a GAM formula

smooth.construct

Constructor functions for smooth terms in a GAM

Overflow proof pdMat class for multiples of the identity matrix

gam.convergence

GAM convergence and performance issues.

Functions for better-than-log positive parameterization

Generalized Additive Mixed Model set up.

Some diagnostics for a fitted gam model.

Prediction/Construction wrapper functions for GAM smooth terms

Specifying Generalized Additive Models.

Generalized Additive Model Selection

Default GAM plotting

Generalized Additive Model default print statement

Objective functions for GAM smoothing parameter estimation.

Extract the diagonal of the Influence/Hat matrix for a GAM.

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

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

Defining smooths in GAM formulae

Alternatives to step.gam

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

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

Define tensor product smooths in GAM formulae

Smallest square root of matrix

Extract the log likelihood for a fitted GAM