パッケージ 'mgcv' の情報
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開始行:
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
終了行:
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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