# mgcv v1.8-18

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## Mixed GAM Computation Vehicle with Automatic Smoothness Estimation

Generalized additive (mixed) models, some of their extensions and
other generalized ridge regression with multiple smoothing
parameter estimation by (REstricted) Marginal Likelihood,
Generalized Cross Validation and similar. Includes a gam()
function, a wide variety of smoothers, JAGS support and
distributions beyond the exponential family.

## Functions in mgcv

Name | Description | |

Rrank | Find rank of upper triangular matrix | |

Sl.initial.repara | Re-parametrizing model matrix X | |

cox.ph | Additive Cox Proportional Hazard Model | |

cox.pht | Additive Cox proportional hazard models with time varying covariates | |

Sl.repara | Applying re-parameterization from log-determinant of penalty matrix to model matrix. | |

Sl.setup | Setting up a list representing a block diagonal penalty matrix | |

bam | Generalized additive models for very large datasets | |

bam.update | Update a strictly additive bam model for new data. | |

dDeta | Obtaining derivative w.r.t. linear predictor | |

exclude.too.far | Exclude prediction grid points too far from data | |

gam.outer | Minimize GCV or UBRE score of a GAM using `outer' iteration | |

gam.reparam | Finding stable orthogonal re-parameterization of the square root penalty. | |

gam2objective | Objective functions for GAM smoothing parameter estimation | |

gamObject | Fitted gam object | |

in.out | Which of a set of points lie within a polygon defined region | |

inSide | Are points inside boundary? | |

formXtViX | Form component of GAMM covariance matrix | |

formula.gam | GAM formula | |

gam | Generalized additive models with integrated smoothness estimation | |

gam.check | Some diagnostics for a fitted gam model | |

ldTweedie | Log Tweedie density evaluation | |

ldetS | Getting log generalized determinant of penalty matrices | |

mroot | Smallest square root of matrix | |

multinom | GAM multinomial logistic regression | |

pdTens | Functions implementing a pdMat class for tensor product smooths | |

Predict.matrix.cr.smooth | Predict matrix method functions | |

Predict.matrix.soap.film | Prediction matrix for soap film smooth | |

cSplineDes | Evaluate cyclic B spline basis | |

choose.k | Basis dimension choice for smooths | |

fix.family.link | Modify families for use in GAM fitting and checking | |

fixDependence | Detect linear dependencies of one matrix on another | |

pen.edf | Extract the effective degrees of freedom associated with each penalty in a gam fit | |

qq.gam | QQ plots for gam model residuals | |

rTweedie | Generate Tweedie random deviates | |

slanczos | Compute truncated eigen decomposition of a symmetric matrix | |

gamlss.gH | Calculating derivatives of log-likelihood wrt regression coefficients | |

gamm | Generalized Additive Mixed Models | |

gevlss | Generalized Extreme Value location-scale model family | |

identifiability | Identifiability constraints | |

mgcv.package | Mixed GAM Computation Vehicle with GCV/AIC/REML smoothness estimation and GAMMs by REML/PQL | |

mgcv.parallel | Parallel computation in mgcv. | |

mini.roots | Obtain square roots of penalty matrices | |

missing.data | Missing data in GAMs | |

betar | GAM beta regression family | |

smooth.construct.sos.smooth.spec | Splines on the sphere | |

smooth.construct.t2.smooth.spec | Tensor product smoothing constructor | |

te | Define tensor product smooths or tensor product interactions in GAM formulae | |

Predict.matrix | Prediction methods for smooth terms in a GAM | |

columb | Reduced version of Columbus OH crime data | |

concurvity | GAM concurvity measures | |

extract.lme.cov | Extract the data covariance matrix from an lme object | |

smooth.construct | Constructor functions for smooth terms in a GAM | |

gam.fit5.post.proc | Post-processing output of gam.fit5 | |

gam.models | Specifying generalized additive models | |

gam.side | Identifiability side conditions for a GAM | |

gam.vcomp | Report gam smoothness estimates as variance components | |

family.mgcv | Distribution families in mgcv | |

gam.control | Setting GAM fitting defaults | |

gam.convergence | GAM convergence and performance issues | |

gam.scale | Scale parameter estimation in GAMs | |

gam.selection | Generalized Additive Model Selection | |

gaulss | Gaussian location-scale model family | |

get.var | Get named variable or evaluate expression from list or data.frame | |

place.knots | Automatically place a set of knots evenly through covariate values | |

plot.gam | Default GAM plotting | |

predict.gam | Prediction from fitted GAM model | |

print.gam | Print a Generalized Additive Model object. | |

ls.size | Size of list elements | |

magic | Stable Multiple Smoothing Parameter Estimation by GCV or UBRE | |

new.name | Obtain a name for a new variable that is not already in use | |

notExp | Functions for better-than-log positive parameterization | |

influence.gam | Extract the diagonal of the influence/hat matrix for a GAM | |

initial.sp | Starting values for multiple smoothing parameter estimation | |

magic.post.proc | Auxilliary information from magic fit | |

mgcv.FAQ | Frequently Asked Questions for package mgcv | |

notExp2 | Alternative to log parameterization for variance components | |

null.space.dimension | The basis of the space of un-penalized functions for a TPRS | |

polys.plot | Plot geographic regions defined as polygons | |

predict.bam | Prediction from fitted Big Additive Model model | |

s | Defining smooths in GAM formulae | |

scat | GAM scaled t family for heavy tailed data | |

smooth.construct.tensor.smooth.spec | Tensor product smoothing constructor | |

smooth.construct.tp.smooth.spec | Penalized thin plate regression splines in GAMs | |

smoothCon | Prediction/Construction wrapper functions for GAM smooth terms | |

tensor.prod.model.matrix | Utility functions for constructing tensor product smooths | |

ziP | GAM zero-inflated Poisson regression family | |

ziplss | Zero inflated Poisson location-scale model family | |

smooth.construct.cr.smooth.spec | Penalized Cubic regression splines in GAMs | |

smooth.construct.ds.smooth.spec | Low rank Duchon 1977 splines | |

smooth.construct.mrf.smooth.spec | Markov Random Field Smooths | |

Tweedie | GAM Tweedie families | |

anova.gam | Approximate hypothesis tests related to GAM fits | |

bandchol | Choleski decomposition of a band diagonal matrix | |

bug.reports.mgcv | Reporting mgcv bugs. | |

mvn | Multivariate normal additive models | |

negbin | GAM negative binomial families | |

ocat | GAM ordered categorical family | |

one.se.rule | The one standard error rule for smoother models | |

smooth.construct.ps.smooth.spec | P-splines in GAMs | |

spasm.construct | Experimental sparse smoothers | |

step.gam | Alternatives to step.gam | |

trind.generator | Generates index arrays for upper triangular storage | |

rig | Generate inverse Gaussian random deviates | |

rmvn | Generate multivariate normal deviates | |

smooth.construct.ad.smooth.spec | Adaptive smooths in GAMs | |

smooth.construct.bs.smooth.spec | Penalized B-splines in GAMs | |

fs.test | FELSPLINE test function | |

full.score | GCV/UBRE score for use within nlm | |

gam.fit | GAM P-IRLS estimation with GCV/UBRE smoothness estimation | |

uniquecombs | find the unique rows in a matrix | |

smooth.construct.re.smooth.spec | Simple random effects in GAMs | |

smooth.construct.so.smooth.spec | Soap film smoother constructer | |

summary.gam | Summary for a GAM fit | |

t2 | Define alternative tensor product smooths in GAM formulae | |

vcov.gam | Extract parameter (estimator) covariance matrix from GAM fit | |

vis.gam | Visualization of GAM objects | |

sp.vcov | Extract smoothing parameter estimator covariance matrix from (RE)ML GAM fit | |

gam.fit3 | P-IRLS GAM estimation with GCV \& UBRE/AIC or RE/ML derivative calculation | |

gamSim | Simulate example data for GAMs | |

gamlss.etamu | Transform derivatives wrt mu to derivatives wrt linear predictor | |

interpret.gam | Interpret a GAM formula | |

jagam | Just Another Gibbs Additive Modeller: JAGS support for mgcv. | |

linear.functional.terms | Linear functionals of a smooth in GAMs | |

logLik.gam | Log likelihood for a fitted GAM, for AIC | |

model.matrix.gam | Extract model matrix from GAM fit | |

mono.con | Monotonicity constraints for a cubic regression spline | |

pcls | Penalized Constrained Least Squares Fitting | |

pdIdnot | Overflow proof pdMat class for multiples of the identity matrix | |

random.effects | Random effects in GAMs | |

residuals.gam | Generalized Additive Model residuals | |

sdiag | Extract or modify diagonals of a matrix | |

single.index | Single index models with mgcv | |

smooth.construct.fs.smooth.spec | Factor smooth interactions in GAMs | |

smooth.construct.gp.smooth.spec | Low rank Gaussian process smooths | |

smooth.terms | Smooth terms in GAM | |

smooth2random | Convert a smooth to a form suitable for estimating as random effect | |

totalPenaltySpace | Obtaining (orthogonal) basis for null space and range of the penalty matrix | |

trichol | Choleski decomposition of a tri-diagonal matrix | |

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## Last month downloads

## Details

Priority | recommended |

LazyLoad | yes |

ByteCompile | yes |

License | GPL (>= 2) |

NeedsCompilation | yes |

Packaged | 2017-07-26 15:00:29 UTC; sw283 |

Repository | CRAN |

Date/Publication | 2017-07-28 07:28:50 UTC |

imports | graphics , Matrix , methods , stats |

suggests | MASS , parallel , splines , survival |

depends | nlme (>= 3.1-64) , R (>= 2.14.0) |

Contributors | Simon Wood |

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