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mgcv (version 1.3-7)

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

1.3-7

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

November 7th, 2025

Functions in mgcv (1.3-7)

Hypothesis tests related to GAM fits

Setting GAM fitting method

Detect linear dependencies of one matrix on another

Specifying Generalized Additive Models.

Setting GAM fitting defaults

Generalized Additive Model default print statement

Extract the formula from a gam object.

Generalized Additive Mixed Models

Smallest square root of matrix

Generalized additive models with integrated smoothness estimation

Extract the log likelihood for a fitted GAM

GCV/UBRE score for use within nlm

Functions for better-than-log positive parameterization

exclude.too.far

Exclude prediction grid points too far from data

magic.post.proc

Auxilliary information from magic fit

Interpret a GAM formula

fix.family.link

Modify families for use in GAM fitting

extract.lme.cov

Extract the data covariance matrix from an lme object

Some diagnostics for a fitted gam model.

gam.convergence

GAM convergence and performance issues.

Define tensor product smooths in GAM formulae

Prediction methods for smooth terms in a GAM

P-IRLS GAM estimation with GCV & UBRE derivative calculation

Generalized Additive Model set up.

Extract parameter (estimator) covariance matrix from GAM fit

Prediction/Construction wrapper functions for GAM smooth terms

find the unique rows in a matrix

Alternative to log parameterization for variance components

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

smooth.construct

Constructor functions for smooth terms in a GAM

Generalized Additive Model residuals

Generalized Additive Mixed Model set up.

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

Overflow proof pdMat class for multiples of the identity matrix

Identifiability side conditions for a GAM.

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

Monotonicity constraints for a cubic regression spline.

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

Starting values for multiple smoothing parameter estimation.

null.space.dimension

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

Summary for a GAM fit

Alternatives to step.gam

GAMs with the negative binomial distribution

Setting mgcv defaults

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

tensor.prod.model.matrix

Utility functions for constructing tensor product smooths

Penalized Constrained Least Squares Fitting

Fitted gam object

Functions implementing a pdMat class for tensor product smooths

Visualization of GAM objects

Automatically place a set of knots evenly through covariate values

Prediction from fitted GAM model

Generalized Additive Model Selection

Form component of GAMM covariance matrix

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

Default GAM plotting

Objective functions for GAM smoothing parameter estimation.

Multiple Smoothing Parameter Estimation by GCV or UBRE

Defining smooths in GAM formulae