パッケージ 'mgcv' の情報

		 パッケージ 'mgcv' の情報 

 記述： 

Package:            mgcv
Version:            1.5-6
Author:             Simon Wood <simon.wood@r-project.org>
Maintainer:         Simon Wood <simon.wood@r-project.org>
Title:              GAMs with GCV/AIC/REML smoothness estimation and
                    GAMMs by PQL
Description:        Routines for GAMs and other generalized ridge
                    regression with multiple smoothing parameter
                    selection by GCV, REML or UBRE/AIC. Also GAMMs by
                    REML or PQL. Includes a gam() function.
Priority:           recommended
Depends:            R (>= 2.3.0)
Imports:            graphics, stats, nlme
Suggests:           nlme (>= 3.1-64), splines
LazyLoad:           yes
License:            GPL (>= 2)
Packaged:           2009-09-11 09:31:19 UTC; simon
Repository:         CRAN
Date/Publication:   2009-09-12 12:18:28
Built:              R 2.10.0; universal-apple-darwin9.8.0; 2009-10-13
                    06:25:24 UTC; unix

 索引： 

mgcv                    Multiple Smoothing Parameter Estimation by GCV or UBRE

anova.gam               Hypothesis tests related to GAM fits
exclude.too.far         Exclude prediction grid points too far from data
extract.lme.cov         Extract the data covariance matrix from an lme object
fixDependence           Detect linear dependencies of one matrix on another
fix.family.link         Modify families for use in GAM fitting
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 with integrated smoothness estimation
gam2objective           Objective functions for GAM smoothing parameter estimation
gam.check               Some diagnostics for a fitted gam model
gam.control             Setting GAM fitting defaults
gam.convergence         GAM convergence and performance issues
gam.fit                 GAM P-IRLS estimation with GCV/UBRE smoothness estimation
gam.fit2                P-IRLS GAM estimation with GCV & UBRE derivative calculation
gamm                    Generalized Additive Mixed Models
gam.method              Setting GAM fitting method
gam.models              Specifying generalized additive models
gamm.setup              Generalized additive mixed model set up
gam.neg.bin             GAMs with the negative binomial distribution
gamObject               Fitted gam object
gam.outer               Minimize GCV or UBRE score of a GAM using 'outer' iteration
gam.selection           Generalized Additive Model Selection
gam.setup               Generalized additive model set up
gam.side                Identifiability side conditions for a GAM
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
initial.sp              Starting values for multiple smoothing parameter estimation
interpret.gam           Interpret a GAM formula
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.control            Setting mgcv defaults
mgcv-package            GAMs with GCV smoothness estimation and GAMMs by REML/PQL
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
notExp2                 Alternative to log parameterization for variance components
null.space.dimension    The basis of the space of un-penalized functions for a TPRS
pcls                    Penalized Constrained Least Squares Fitting
pdIdnot                 Overflow proof pdMat class for multiples of the identity matrix
pdTens                  Functions implementing a pdMat class for tensor product smooths
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
print.gam               Generalized Additive Model default print statement
residuals.gam           Generalized Additive Model residuals
s                       Defining smooths in GAM formulae
smoothCon               Prediction/Construction wrapper functions for GAM smooth terms
smooth.construct        Constructor functions for smooth terms in a GAM
step.gam                Alternatives to step.gam
summary.gam             Summary for a GAM fit
te                      Define tensor product smooths in GAM formulae
tensor.prod.model.matrix Utility functions for constructing tensor product smooths
uniquecombs             find the unique rows in a matrix
vcov.gam                Extract parameter (estimator) covariance matrix from GAM fit
vis.gam                 Visualization of GAM objects

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