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mgcv (version 1.3-6)

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

481,715

Version

1.3-6

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

April 4th, 2025

Functions in mgcv (1.3-6)

Detect linear dependencies of one matrix on another

Identifiability side conditions for a GAM.

exclude.too.far

Exclude prediction grid points too far from data

Some diagnostics for a fitted gam model.

Form component of GAMM covariance matrix

Multiple Smoothing Parameter Estimation by GCV or UBRE

Prediction methods for smooth terms in a GAM

GCV/UBRE score for use within nlm

Fitted gam object

gam.convergence

GAM convergence and performance issues.

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

extract.lme.cov

Extract the data covariance matrix from an lme object

fix.family.link

Modify families for use in GAM fitting

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

Setting GAM fitting method

P-IRLS GAM estimation with GCV & UBRE derivative calculation

Setting GAM fitting defaults

Generalized Additive Model set up.

Extract the log likelihood for a fitted GAM

Specifying Generalized Additive Models.

Generalized Additive Mixed Models

Interpret a GAM formula

Objective functions for GAM smoothing parameter estimation.

Generalized Additive Model Selection

Generalized Additive Mixed Model set up.

Extract the formula from a gam object.

Starting values for multiple smoothing parameter estimation.

Hypothesis tests related to GAM fits

Generalized additive models with integrated smoothness estimation

smooth.construct

Constructor functions for smooth terms in a GAM

magic.post.proc

Auxilliary information from magic fit

Prediction/Construction wrapper functions for GAM smooth terms

Setting mgcv defaults

GAMs with the negative binomial distribution

Automatically place a set of knots evenly through covariate values

tensor.prod.model.matrix

Utility functions for constructing tensor product smooths

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

Monotonicity constraints for a cubic regression spline.

Alternatives to step.gam

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

Functions implementing a pdMat class for tensor product smooths

Alternative to log parameterization for variance components

Visualization of GAM objects

Summary for a GAM fit

Generalized Additive Model residuals

Smallest square root of matrix

Penalized Constrained Least Squares Fitting

Functions for better-than-log positive parameterization

null.space.dimension

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

Prediction from fitted GAM model

Extract parameter (estimator) covariance matrix from GAM fit

Generalized Additive Model default print statement

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

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

Overflow proof pdMat class for multiples of the identity matrix

Define tensor product smooths in GAM formulae

Defining smooths in GAM formulae

Default GAM plotting

find the unique rows in a matrix