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