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| gam | Generalized Additive Models using penalized regression splines and GCV |
| gam.control | Setting Generalized Additive Models fitting defaults |
| gam.fit | Generalized Additive Models fitting using penalized regression splines and GCV |
| 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.setup | Generalized Additive Model set up. |
| GAMsetup | Set up GAM using penalized cubic 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.dimension | Dimension of the space of un-penalized functions. |
| 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 |
| SANtest | Example of simple additive GAM using penalized regression splines. |
| 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 |