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| anova.gam | Hypothesis tests related to GAM fits |
| coef.pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| coef.pdTens | Functions implementing a pdMat class for tensor product smooths |
| corMatrix.pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| Dim.pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| exclude.too.far | Exclude prediction grid points too far from data |
| extract.lme.cov | Extract the data covariance matrix from an lme object |
| extract.lme.cov2 | Extract the data covariance matrix from an lme object |
| formula.gam | Extract the formula from a gam object. |
| formXtViX | Form component of GAMM covariance matrix |
| full.score | GCV/UBRE score for use within nlm |
| gam | Generalized Additive Models using penalized regression splines and GCV |
| gam.check | Some diagnostics for a fitted gam model. |
| gam.control | Setting GAM fitting defaults |
| gam.convergence | GAM convergence issues. |
| gam.fit | Generalized Additive Models fitting using penalized regression splines and GCV |
| gam.models | Specifying generalized Additive Models. |
| gam.neg.bin | GAMs with the negative binomial distribution |
| gam.selection | Generalized Additive Model Selection |
| gam.setup | Generalized Additive Model set up. |
| gam.side.conditions | Identifiability side conditions for a GAM. |
| gamm | Generalized Additive Mixed Models |
| gamm.setup | Generalized Additive Mixed Model set up. |
| gamObject | Fitted gam object |
| get.var | Get named variable or evaluate expression from list or data.frame |
| influence.gam | Extract the diagonal of the Influence/Hat matrix for a GAM. |
| interpret.gam | Interpret a GAM formula |
| logDet.pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| logLik.gam | Extract the log likelihood for a fitted GAM |
| magic | Stable Multiple Smoothing Parameter Estimation by GCV or UBRE, with optional fixed penalty |
| magic.post.proc | Auxilliary information from magic fit |
| mgcv | Multiple Smoothing Parameter Estimation by GCV or UBRE |
| mgcv.control | Setting mgcv defaults |
| mgcv.find.theta | GAMs with the negative binomial distribution |
| mgcv.get.scale | GAMs with the negative binomial distribution |
| mono.con | Monotonicity constraints for a cubic regression spline. |
| mroot | Smallest square root of matrix |
| new.name | Obtain a name for a new variable that is not already in use |
| notExp | Functions for better-than-log positive parameterization |
| notLog | Functions for better-than-log positive parameterization |
| 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. |
| p.spline | Constructor functions for smooth terms in a GAM |
| pcls | Penalized Constrained Least Squares Fitting |
| pdConstruct.pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| pdConstruct.pdTens | Functions implementing a pdMat class for tensor product smooths |
| pdFactor.pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| pdFactor.pdTens | Functions implementing a pdMat class for tensor product smooths |
| pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| pdMatrix.pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| pdMatrix.pdTens | Functions implementing a pdMat class for tensor product smooths |
| pdTens | Functions implementing a pdMat class for tensor product smooths |
| persp.gam | Visualization of GAM objects |
| place.knots | Automatically place a set of knots evenly through covariate values |
| plot.gam | Default GAM plotting |
| predict.gam | Prediction from fitted GAM model |
| Predict.matrix | Prediction methods for smooth terms in a GAM |
| Predict.matrix.cr.smooth | Prediction methods for smooth terms in a GAM |
| Predict.matrix.cs.smooth | Prediction methods for smooth terms in a GAM |
| Predict.matrix.cyclic.smooth | Prediction methods for smooth terms in a GAM |
| Predict.matrix.tensor.smooth | Prediction methods for smooth terms in a GAM |
| Predict.matrix.tprs.smooth | Prediction methods for smooth terms in a GAM |
| Predict.matrix.ts.smooth | Prediction methods for smooth terms in a GAM |
| print.anova.gam | Hypothesis tests related to GAM fits |
| print.gam | Generalized Additive Model default print statement |
| print.summary.gam | Summary for a GAM fit |
| residuals.gam | Generalized Additive Model residuals |
| s | Defining smooths in GAM formulae |
| smooth.construct | Constructor functions for smooth terms in a GAM |
| smooth.construct.cc.smooth.spec | Constructor functions for smooth terms in a GAM |
| smooth.construct.cr.smooth.spec | Constructor functions for smooth terms in a GAM |
| smooth.construct.cs.smooth.spec | Constructor functions for smooth terms in a GAM |
| smooth.construct.tensor.smooth.spec | Constructor functions for smooth terms in a GAM |
| smooth.construct.tp.smooth.spec | Constructor functions for smooth terms in a GAM |
| smooth.construct.ts.smooth.spec | Constructor functions for smooth terms in a GAM |
| solve.pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| step.gam | Alternatives to step.gam |
| summary.gam | Summary for a GAM fit |
| summary.pdIdnot | Overflow proof pdMat class for multiples of the identity matrix |
| summary.pdTens | Functions implementing a pdMat class for tensor product smooths |
| te | Define tensor product smooths in GAM formulae |
| tensor.prod.model.matrix | Utility functions for constructing tensor product smooths |
| tensor.prod.penalties | Utility functions for constructing tensor product smooths |
| uniquecombs | find the unique rows in a matrix |
| vis.gam | Visualization of GAM objects |