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mgcv (version 1.0-5)

Multiple smoothing parameter estimation and GAMs by GCV

Description

Routines for GAMs, GAMMs and other generalized ridge regression with multiple smoothing parameter selection by GCV or UBRE. Includes an implementation (not a clone) of gam().

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Version

Install

install.packages('mgcv')

Monthly Downloads

481,715

Version

1.0-5

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

April 4th, 2025

Functions in mgcv (1.0-5)

full.score

GCV/UBRE score for use within nlm
gam.selection

Generalized Additive Model Selection
get.var

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

Specifying generalized Additive Models.
gam.side.conditions

Identifiability side conditions for a GAM.
residuals.gam

Generalized Additive Model residuals
mgcv

Multiple Smoothing Parameter Estimation by GCV or UBRE
gamm.setup

Generalized Additive Mixed Model set up.
smooth.construct

Constructor functions for smooth terms in a GAM
magic

Stable Multiple Smoothing Parameter Estimation by GCV or UBRE, with optional fixed penalty
extract.lme.cov

Extract the data covariance matrix from an lme object
gam

Generalized Additive Models using penalized regression splines and GCV
uniquecombs

find the unique rows in a matrix
magic.post.proc

Auxilliary information from magic fit
Predict.matrix

Prediction methods for smooth terms in a GAM
interpret.gam

Interpret a GAM formula
null.space.dimension

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

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

Some diagnostics for a fitted gam model.
gam.fit

Generalized Additive Models fitting using penalized regression splines and GCV
print.gam

Generalized Additive Model default print statement
new.name

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

Penalized Constrained Least Squares Fitting
gam.control

Setting GAM fitting defaults
exclude.too.far

Exclude prediction grid points too far from data
gam.setup

Generalized Additive Model set up.
pdTens

Functions implementing a pdMat class for tensor product smooths
notExp

Functions for better-than-log positive parameterization
gamm

Generalized Additive Mixed Models
gam.neg.bin

GAMs with the negative binomial distribution
mono.con

Monotonicity constraints for a cubic regression spline.
te

Define tensor product smooths in GAM formulae
tensor.prod.model.matrix

Utility functions for constructing tensor product smooths
mroot

Smallest square root of matrix
plot.gam

Default GAM plotting
place.knots

Automatically place a set of knots evenly through covariate values
predict.gam

Prediction from fitted GAM model
mgcv.control

Setting mgcv defaults
summary.gam

Summary for a GAM fit
s

Defining smooths in GAM formulae
vis.gam

Visualization of GAM objects