Multiple smoothing parameter estimation and GAMs by GCV


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gam Generalized Additive Models using penalized regression splines and GCV
gam.check Some diagnostics for a fitted gam model.
gam.control Setting Generalized Additive Models fitting defaults
gam.fit Generalized Additive Models fitting using penalized regression splines and GCV
gam.models Specifying generalized Additive Models.
gam.nbut Generalized Additive Models using Negative Binomial errors with unknown theta
gam.parser Generalized Additive Model fitting using penalized regression splines and GCV
gam.selection Generalized Additive Model Selection
gam.setup Generalized Additive Model set up.
gam.side.conditions Identifiability side conditions for a GAM.
GAMsetup Set up GAM using penalized regression splines
get.family Identifies families
mgcv Multiple Smoothing Parameter Estimation by GCV or UBRE
mono.con Monotonicity constraints for a cubic regression spline.
neg.binom Family function for Negative Binomial GAMs
null.space.basis.labels The basis of the space of un-penalized functions for a t.p.r.s.
null.space.basis.powers The basis of the space of un-penalized functions for a t.p.r.s.
null.space.dimension The basis of the space of un-penalized functions for a t.p.r.s.
pcls Penalized Constrained Least Squares Fitting
persp.gam Perspective Plot of GAM objects
plot.gam Default GAM plotting
predict.gam Prediction from fitted GAM model
print.gam Generalized Additive Model default print statement
print.summary.gam Summary for a GAM fit
QT QT factorisation of a matrix
residuals.gam Generalized Additive Model residuals
s Defining smooths in GAM formulae
summary.gam Summary for a GAM fit
theta.maxl Estimate theta of the Negative Binomial by Maximum Likelihood
uniquecombs find the unique rows in a matrix