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mgcv (version 0.8-3)

Multiple smoothing parameter estimation and GAMs by GCV

Description

Routines for GAMs and other generalized ridge regression problems 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

97,913

Version

0.8-3

License

GPL version 2 or later

Maintainer

Simon Wood

Last Published

November 7th, 2025

Functions in mgcv (0.8-3)

Family function for Negative Binomial GAMs

Default GAM plotting

Generalized Additive Models using Negative Binomial errors with unknown theta

Generalized Additive Models using penalized regression splines and GCV

Generalized Additive Model Selection

Setting Generalized Additive Models fitting defaults

Multiple Smoothing Parameter Estimation by GCV or UBRE

Identifies families

Monotonicity constraints for a cubic regression spline.

Prediction from fitted GAM model

Generalized Additive Model fitting using penalized regression splines and GCV

Estimate theta of the Negative Binomial by Maximum Likelihood

Set up GAM using penalized regression splines

Summary for a GAM fit

Perspective Plot of GAM objects

QT factorisation of a matrix

Defining smooths in GAM formulae

null.space.dimension

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

Generalized Additive Model set up.

Generalized Additive Model residuals

Some diagnostics for a fitted gam model.

Generalized Additive Models fitting using penalized regression splines and GCV

Specifying generalized Additive Models.

Generalized Additive Model default print statement

gam.side.conditions

Identifiability side conditions for a GAM.

find the unique rows in a matrix

Penalized Constrained Least Squares Fitting