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： 
 
 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                    Multiple Smoothing Parameter Estimation by GCV
                         or UBRE
 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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