Generalized Additive Mixed Models
GAM convergence and performance issues.
Specifying Generalized Additive Models.
Form component of GAMM covariance matrix
Exclude prediction grid points too far from data
Objective functions for GAM smoothing parameter estimation.
Generalized Additive Model set up.
Identifiability side conditions for a GAM.
Some diagnostics for a fitted gam model.
Setting GAM fitting method
Prediction methods for smooth terms in a GAM
Generalized Additive Model Selection
Obtain a name for a new variable that is not already in use
Generalized Additive Mixed Model set up.
Extract the log likelihood for a fitted GAM
Extract the formula from a gam object.
Auxilliary information from magic fit
Automatically place a set of knots evenly through covariate values
GAMs with the negative binomial distribution
Interpret a GAM formula
Defining smooths in GAM formulae
Prediction from fitted GAM model
Penalized Constrained Least Squares Fitting
Starting values for multiple smoothing parameter estimation.
find the unique rows in a matrix
Functions implementing a pdMat class for tensor product smooths
P-IRLS GAM estimation with GCV & UBRE derivative calculation
Extract the data covariance matrix from an lme object
GCV/UBRE score for use within nlm
Prediction/Construction wrapper functions for GAM smooth terms
Modify families for use in GAM fitting
Get named variable or evaluate expression from list or data.frame
Stable Multiple Smoothing Parameter Estimation by GCV or UBRE,
with optional fixed penalty
Minimize GCV or UBRE score of a GAM using `outer' iteration
Constructor functions for smooth terms in a GAM
Summary for a GAM fit
Setting mgcv defaults
The basis of the space of un-penalized functions for a t.p.r.s.
Utility functions for constructing tensor product smooths
Smallest square root of matrix
Overflow proof pdMat class for multiples of the identity matrix
Monotonicity constraints for a cubic regression spline.
Extract parameter (estimator) covariance matrix from GAM fit
Default GAM plotting
Setting GAM fitting defaults
Functions for better-than-log positive parameterization
Detect linear dependencies of one matrix on another
Generalized additive models with integrated smoothness estimation
Multiple Smoothing Parameter Estimation by GCV or UBRE
Generalized Additive Model residuals
Hypothesis tests related to GAM fits
Extract the diagonal of the Influence/Hat matrix for a GAM.
GAM P-IRLS estimation with GCV/UBRE smoothness estimation.
Define tensor product smooths in GAM formulae
Alternatives to step.gam
Fitted gam object
Generalized Additive Model default print statement
Visualization of GAM objects