# mgcv v1.8-33

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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, or using iterated
nested Laplace approximation for fully Bayesian inference. See
Wood (2017) <doi:10.1201/9781315370279> for an overview.
Includes a gam() function, a wide variety of smoothers, 'JAGS'
support and distributions beyond the exponential family.

## Functions in mgcv

Name | Description | |

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

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

Sl.inirep | Re-parametrizing model matrix X | |

betar | GAM beta regression family | |

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

Tweedie | GAM Tweedie families | |

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

FFdes | Level 5 fractional factorial designs | |

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

Rrank | Find rank of upper triangular matrix | |

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

choose.k | Basis dimension choice for smooths | |

choldrop | Deletion and rank one Cholesky factor update | |

cSplineDes | Evaluate cyclic B spline basis | |

blas.thread.test | BLAS thread safety | |

bandchol | Choleski decomposition of a band diagonal matrix | |

cox.ph | Additive Cox Proportional Hazard Model | |

family.mgcv | Distribution families in mgcv | |

bam | Generalized additive models for very large datasets | |

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

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

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

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

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

XWXd | Internal functions for discretized model matrix handling | |

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

columb | Reduced version of Columbus OH crime data | |

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

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

concurvity | GAM concurvity measures | |

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

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

fs.test | FELSPLINE test function | |

gam.convergence | GAM convergence and performance issues | |

gam | Generalized additive models with integrated smoothness estimation | |

gam.control | Setting GAM fitting defaults | |

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

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

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

formXtViX | Form component of GAMM covariance matrix | |

gamm | Generalized Additive Mixed Models | |

gam.mh | Simple posterior simulation with gam fits | |

gammals | Gamma location-scale model family | |

gaulss | Gaussian location-scale model family | |

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

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

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

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

formula.gam | GAM formula | |

gam.selection | Generalized Additive Model Selection | |

gumbls | Gumbel location-scale model family | |

identifiability | Identifiability constraints | |

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

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

gam.scale | Scale parameter estimation in GAMs | |

ginla | GAM Integrated Nested Laplace Approximation Newton Enhanced | |

k.check | Checking smooth basis dimension | |

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

ldTweedie | Log Tweedie density evaluation | |

gamObject | Fitted gam object | |

gam.models | Specifying generalized additive models | |

ls.size | Size of list elements | |

multinom | GAM multinomial logistic regression | |

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

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

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

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

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

mgcv.parallel | Parallel computation in mgcv. | |

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

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

missing.data | Missing data in GAMs | |

gam2objective | Objective functions for GAM smoothing parameter estimation | |

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

interpret.gam | Interpret a GAM formula | |

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

gamSim | Simulate example data for GAMs | |

pcls | Penalized Constrained Least Squares Fitting | |

psum.chisq | Evaluate the c.d.f. of a weighted sum of chi-squared deviates | |

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

mvn | Multivariate normal additive models | |

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

plot.gam | Default GAM plotting | |

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

predict.gam | Prediction from fitted GAM model | |

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

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

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

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

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

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

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

notExp2 | Alternative to log parameterization for variance components | |

s | Defining smooths in GAM formulae | |

ldetS | Getting log generalized determinant of penalty matrices | |

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

mroot | Smallest square root of matrix | |

ocat | GAM ordered categorical family | |

inSide | Are points inside boundary? | |

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

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

sdiag | Extract or modify diagonals of a matrix | |

negbin | GAM negative binomial families | |

shash | Sinh-arcsinh location scale and shape model family | |

residuals.gam | Generalized Additive Model residuals | |

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

random.effects | Random effects in GAMs | |

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

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

single.index | Single index models with mgcv | |

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

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

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

rTweedie | Generate Tweedie random deviates | |

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

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

summary.gam | Summary for a GAM fit | |

rig | Generate inverse Gaussian random deviates | |

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

rmvn | Generate from or evaluate multivariate normal or t densities. | |

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

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

uniquecombs | find the unique rows in a matrix | |

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

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

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

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

vis.gam | Visualization of GAM objects | |

smooth.info | Generic function to provide extra information about smooth specification | |

spasm.construct | Experimental sparse smoothers | |

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

step.gam | Alternatives to step.gam | |

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

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

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

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

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

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

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

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

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

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

ziplss | Zero inflated (hurdle) Poisson location-scale model family | |

twlss | Tweedie location scale family | |

tensor.prod.model.matrix | Row Kronecker product/ tensor product smooth construction | |

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

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 | |

smooth.terms | Smooth terms in GAM | |

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

ziP | GAM zero-inflated (hurdle) Poisson regression family | |

No Results! |

## Last month downloads

## Details

Priority | recommended |

LazyLoad | yes |

ByteCompile | yes |

License | GPL (>= 2) |

NeedsCompilation | yes |

Packaged | 2020-08-24 19:32:32 UTC; sw283 |

Repository | CRAN |

Date/Publication | 2020-08-27 08:30:02 UTC |

imports | graphics , Matrix , methods , splines , stats , utils |

suggests | MASS , parallel , survival |

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

Contributors | Simon Wood |

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