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mgcv (version 1.2-6)

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

121,780

Version

1.2-6

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

April 4th, 2025

Functions in mgcv (1.2-6)

Generalized Additive Model set up.

Generalized Additive Mixed Model set up.

Generalized additive models with integrated smoothness estimation

Penalized Constrained Least Squares Fitting

Multiple Smoothing Parameter Estimation by GCV or UBRE

Specifying Generalized Additive Models.

Fitted gam object

Extract the formula from a gam object.

Generalized Additive Model Selection

Functions for better-than-log positive parameterization

Starting values for multiple smoothing parameter estimation.

Overflow proof pdMat class for multiples of the identity matrix

Define tensor product smooths in GAM formulae

Extract the log likelihood for a fitted GAM

Default GAM plotting

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

Setting GAM fitting defaults

Detect linear dependencies of one matrix on another

Functions implementing a pdMat class for tensor product smooths

fix.family.link

Modify families for use in GAM fitting

P-IRLS GAM estimation with GCV & UBRE derivative calculation

gam.convergence

GAM convergence and performance issues.

Defining smooths in GAM formulae

Generalized Additive Model residuals

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

null.space.dimension

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

Monotonicity constraints for a cubic regression spline.

tensor.prod.model.matrix

Utility functions for constructing tensor product smooths

Generalized Additive Model default print statement

magic.post.proc

Auxilliary information from magic fit

Smallest square root of matrix

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

Setting mgcv defaults

Form component of GAMM covariance matrix

Some diagnostics for a fitted gam model.

Setting GAM fitting method

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

Objective functions for GAM smoothing parameter estimation.

Summary for a GAM fit

find the unique rows in a matrix

Visualization of GAM objects

Prediction from fitted GAM model

extract.lme.cov

Extract the data covariance matrix from an lme object

Identifiability side conditions for a GAM.

Alternatives to step.gam

Extract parameter (estimator) covariance matrix from GAM fit

Automatically place a set of knots evenly through covariate values

Prediction/Construction wrapper functions for GAM smooth terms

Prediction methods for smooth terms in a GAM

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

GCV/UBRE score for use within nlm

Hypothesis tests related to GAM fits

exclude.too.far

Exclude prediction grid points too far from data

Generalized Additive Mixed Models

GAMs with the negative binomial distribution

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

Interpret a GAM formula

smooth.construct

Constructor functions for smooth terms in a GAM