fda.usc: Functional Data Analysis and Utilities for Statistical Computing

Routines for exploratory and descriptive analysis of functional data such as depth measurements, atypical curves detection, regression models, supervised classification, unsupervised classification and functional analysis of variance.

AuthorManuel Febrero Bande [aut], Manuel Oviedo de la Fuente [aut, cre], Pedro Galeano [ctb], Alicia Nieto [ctb], Eduardo Garcia-Portugues [ctb]
Date of publication2016-11-14 12:33:41
MaintainerManuel Oviedo de la Fuente <manuel.oviedo@usc.es>
LicenseGPL-2
Version1.3.0
http://www.jstatsoft.org/v51/i04/

View on CRAN

Man pages

aemet: aemet data

anova.hetero: ANOVA for heteroscedastic data

anova.onefactor: One-way anova model for functional data

anova.RPm: Functional ANOVA with Random Project.

classif.DD: DD-Classifier Based on DD-plot

classif.depth: Classifier from Functional Data

classif.gkam: Classification Fitting Functional Generalized Kernel Additive...

classif.glm: Classification Fitting Functional Generalized Linear Models

classif.gsam: Classification Fitting Functional Generalized Additive Models

classif.np: Kernel Classifier from Functional Data

classif.tree: Classification Fitting Functional Recursive Partitioning and...

cond.F: Conditional Distribution Function

cond.mode: Conditional mode

cond.quantile: Conditional quantile

create.fdata.basis: Create Basis Set for Functional Data of fdata class

CV.S: The cross-validation (CV) score

DepthFunctional: Provides the depth measure for functional data

DepthFunctionalIntegrate: Provides the depth measure for a list of p-functional data...

DepthMultivariate: Provides the depth measure for multivariate data

Descriptive: Descriptive measures for functional data.

dev.S: The deviance score .

dfv.test: Delsol, Ferraty and Vieu test for no functional-scalar...

dis.cos.cor: Proximities between functional data

fdata: Converts raw data or other functional data classes into fdata...

fdata2fd: Converts fdata class object into fd class object

fdata2pc: Principal components for functional data

fdata2pls: Partial least squares components for functional data.

fdata.bootstrap: Bootstrap samples of a functional statistic

fdata.cen: Functional data centred (subtract the mean of each...

fdata.deriv: Computes the derivative of functional data object.

fdata.methods: fdata S3 Group Generic Functions

fda.usc.internal: fda.usc internal functions

fda.usc-package: Functional Data Analysis and Utilities for Statistical...

FDR: False Discorvery Rate (FDR)

flm.Ftest: F-test for the Functional Linear Model with scalar response

flm.test: Goodness-of-fit test for the Functional Linear Model with...

fregre.basis: Functional Regression with scalar response using basis...

fregre.basis.cv: Cross-validation Functional Regression with scalar response...

fregre.basis.fr: Functional Regression with functional response using basis...

fregre.bootstrap: Bootstrap regression

fregre.gkam: Fitting Functional Generalized Kernel Additive Models.

fregre.glm: Fitting Functional Generalized Linear Models

fregre.gls: Fit Functional Linear Model Using Generalized Least Squares

fregre.gsam: Fitting Functional Generalized Spectral Additive Models

fregre.igls: Fit of Functional Generalized Least Squares Model Iteratively

fregre.lm: Fitting Functional Linear Models

fregre.np: Functional regression with scalar response using...

fregre.np.cv: Cross-validation functional regression with scalar response...

fregre.pc: Functional Regression with scalar response using Principal...

fregre.pc.cv: Functional penalized PC regression with scalar response using...

fregre.plm: Semi-functional partially linear model with scalar response.

fregre.pls: Functional Penalized PLS regression with scalar response

fregre.pls.cv: Functional penalized PLS regression with scalar response...

fregre.ppls: Functional Penalized PC (or PLS) regression with scalar...

fregre.ppls.cv: Functional penalized PC (or PLS) regression with scalar...

GCCV.S: The generalized correlated cross-validation (GCCV) score.

GCV.S: The generalized cross-validation (GCV) score.

gridfdata: Utils for generate functional data

h.default: Calculation of the smoothing parameter (h) for a functional...

influence.fdata: Functional influence measures

influence.quan: Quantile for influence measures

inprod.fdata: Inner products of Functional Data Objects o class (fdata)

int.simpson: Simpson integration

Kernel: Symmetric Smoothing Kernels.

Kernel.asymmetric: Asymmetric Smoothing Kernel

Kernel.integrate: Integrate Smoothing Kernels.

kmeans.fd: K-Means Clustering for functional data

MCO: Mithochondiral calcium overload (MCO) data set

metric.dist: Distance Matrix Computation

metric.hausdorff: Compute the Hausdorff distances between two curves.

metric.kl: Kullback-Leibler distance

metric.lp: Aproximates Lp-metric distances for functional data.

min.basis: Select the number of basis using GCV method.

min.np: Smoothing of functional data using nonparametric kernel...

norm.fdata: Aproximates Lp-norm for functional data.

order.fdata: A wrapper for the 'order' function

Outliers.fdata: Detecting outliers for functional dataset

PCvM.statistic: PCvM statistic for the Functional Linear Model with scalar...

phoneme: phoneme data

plot.fdata: Plot functional data: fdata.

poblenou: poblenou data

P.penalty: Penalty matrix for higher order differences

predict.classif: Predicts from a fitted classif object.

predict.classif.DD: Predicts from a fitted classif.DD object.

predict.fregre.fd: Predict method for functional linear model (fregre.fd class)

predict.fregre.functional: Predict method for functional response model

predict.fregre.gls: Predictions from a functional gls object

predict.fregre.scalar: Predict method for functional regression model

rp.flm.statistic: Statistic for testing the FLM using random projections

rp.flm.test: Goodness-of-fit test for the Functional Linear Model with...

rproc2fdata: Simulate several random processes.

rwild: Wild bootstrap residuals

S.basis: Smoothing matrix with roughness penalties by basis...

semimetric.basis: Proximities between functional data

semimetric.NPFDA: Proximities between functional data (semi-metrics)

S.np: Smoothing matrix by nonparametric methods.

split_omit.fdata: A wrapper for the split and unlist function for fdata object

subset.fdata: Subsetting

summary.classif: Summarizes information from kernel classification methods.

summary.fdata.comp: Correlation for functional data by Principal Component...

summary.fregre.fd: Summarizes information from fregre.fd objects.

summary.fregre.gkam: Summarizes information from fregre.gkam objects.

tecator: tecator data

Var.y: Sampling Variance estimates

Files in this package

fda.usc
fda.usc/inst
fda.usc/inst/CITATION
fda.usc/inst/script
fda.usc/inst/script/jss757.R
fda.usc/inst/script/flm_beta_estimation_brownian_data.R
fda.usc/inst/script/Outliers_fdata.R
fda.usc/src
fda.usc/src/rp_stat.f90
fda.usc/src/Adot.f90
fda.usc/src/PCvM_statistic.f90
fda.usc/NAMESPACE
fda.usc/NEWS
fda.usc/data
fda.usc/data/tecator.rda
fda.usc/data/poblenou.rda
fda.usc/data/aemet.rda
fda.usc/data/MCO.rda
fda.usc/data/phoneme.rda
fda.usc/data/datalist
fda.usc/R
fda.usc/R/predict.fregre.gkam.R fda.usc/R/rp.flm.test2.R fda.usc/R/cond.quantile.R
fda.usc/R/func.mean.formula.r
fda.usc/R/influence.fdata.R fda.usc/R/fregre.plm.R
fda.usc/R/fregre.igls.r
fda.usc/R/is.fdata.R
fda.usc/R/print.fregre.fd.r
fda.usc/R/fregre.gls.r
fda.usc/R/fregre.basis.cv.R fda.usc/R/anova.hetero.R
fda.usc/R/metric.kl.r
fda.usc/R/fdata.deriv.R
fda.usc/R/depth.RPD.r
fda.usc/R/depth.FM.r
fda.usc/R/predict.fregre.glm.R
fda.usc/R/fdata.bootstrap.r
fda.usc/R/Descriptive.R fda.usc/R/corStruct.R
fda.usc/R/fregre.lm.r
fda.usc/R/split.fdata.r
fda.usc/R/predict.fregre.igls.r
fda.usc/R/CV.S.R fda.usc/R/min.basis.R fda.usc/R/fregre.gsam.R fda.usc/R/S.basis.R fda.usc/R/semimetric.basis.R fda.usc/R/S.KNN.R fda.usc/R/metric.hausdorff.R
fda.usc/R/par.fda.usc.r
fda.usc/R/semimetric.NPFDA.r
fda.usc/R/dev.S.R
fda.usc/R/print.classif.r
fda.usc/R/kmeans.fd.R
fda.usc/R/depth.RPp.r
fda.usc/R/fregre.basis.fr.r
fda.usc/R/omit.fdata.R fda.usc/R/plot.fdata.R fda.usc/R/anova.onefactor.R fda.usc/R/rproc2fdata.R
fda.usc/R/fregre.np.r
fda.usc/R/predict.gls.nlme.r
fda.usc/R/flm.test.R fda.usc/R/kmeans.center.ini.R
fda.usc/R/depth.RP.r
fda.usc/R/metric.dist.R
fda.usc/R/depth.mode.r
fda.usc/R/dis.cos.cor.R fda.usc/R/depth.SD.R fda.usc/R/anova.RPm.boot.R fda.usc/R/fdata.R fda.usc/R/GCV.S.R
fda.usc/R/dcor.fdist.r
fda.usc/R/outliers.depth.trim.r
fda.usc/R/fdata.methods.R
fda.usc/R/norm.fdata.r
fda.usc/R/plot.lfdata.R fda.usc/R/summary.classif.R fda.usc/R/classif.gkam.R fda.usc/R/FDR.R
fda.usc/R/depth.RT.r
fda.usc/R/create.fdata.basis.R
fda.usc/R/predict.fregre.fd.r
fda.usc/R/classif.glm.R fda.usc/R/S.LLR.R fda.usc/R/Var.y.R fda.usc/R/metric.lp.R fda.usc/R/predict.fregre.gsam.R fda.usc/R/inprod.fdata.R
fda.usc/R/fregre.gkam.r
fda.usc/R/outliers.depth.pond.r
fda.usc/R/Kernel.asymmetric.R
fda.usc/R/classif.DD.r
fda.usc/R/predict.fregre.fr.r
fda.usc/R/depth.multivariate.R fda.usc/R/fdata2fd.R fda.usc/R/kernels.R fda.usc/R/traza.R
fda.usc/R/fregre.bootstrap.r
fda.usc/R/classif.depth.R fda.usc/R/kmeans.assig.groups.R fda.usc/R/corSigma.R fda.usc/R/predict.classif.npp.R
fda.usc/R/predict.fregre.gls.r
fda.usc/R/predict.classif.R
fda.usc/R/classif.np.r
fda.usc/R/h.default.R fda.usc/R/fregre.PPC.PPLSdeprecated.R fda.usc/R/classif.univariate.R fda.usc/R/influence.quan.R
fda.usc/R/quantile.outliers.trim.r
fda.usc/R/depth.band.r
fda.usc/R/fdata.cen.R fda.usc/R/cond.mode.R fda.usc/R/depth.KFSD.R fda.usc/R/anova.RPm.R
fda.usc/R/outliers.lrt.r
fda.usc/R/outliers.thres.lrt.r
fda.usc/R/summary.anova.R fda.usc/R/subset.lfdata.R fda.usc/R/auxiliar.R fda.usc/R/classif.tree.R fda.usc/R/Kernel.R fda.usc/R/flm.Ftest.R fda.usc/R/kmeans.centers.update.R
fda.usc/R/fregre.np.cv.r
fda.usc/R/cond.F.R
fda.usc/R/dcor.fdist2.r
fda.usc/R/fregre.glm.R fda.usc/R/predict.classif.DD.R fda.usc/R/GCCV.S.R fda.usc/R/predict.fregre.plm.R
fda.usc/R/min.np.r
fda.usc/R/summary.fregre.fd.r
fda.usc/R/summary.fdata.comp.r
fda.usc/R/PPC.PPLS.R
fda.usc/R/classif.DD.aux.r
fda.usc/R/order.fdata.r
fda.usc/R/plot.bifd.R fda.usc/R/classif.np.ldata.R fda.usc/R/predict.fregre.lm.R fda.usc/R/classif.gsam.R fda.usc/R/int.simpson.R fda.usc/R/fda.usc.internal.R fda.usc/R/na.omit.fdata.R fda.usc/R/S.NW.R fda.usc/R/fregre.PPC.PPLS.R
fda.usc/R/quantile.outliers.pond.r
fda.usc/R/Ginv.R
fda.usc/R/Var.e.r
fda.usc/R/fregre.basis.R fda.usc/R/dfv.test.R
fda.usc/MD5
fda.usc/DESCRIPTION
fda.usc/man
fda.usc/man/anova.RPm.Rd fda.usc/man/fregre.pls.Rd fda.usc/man/metric.dist.Rd fda.usc/man/dis.cos.cor.Rd fda.usc/man/metric.hausdorff.Rd fda.usc/man/Kernel.asymmetric.Rd fda.usc/man/summary.fdata.comp.Rd fda.usc/man/fda.usc.internal.Rd fda.usc/man/fregre.gls.Rd fda.usc/man/fregre.gsam.Rd fda.usc/man/dfv.test.Rd fda.usc/man/predict.fregre.functional.Rd fda.usc/man/S.np.Rd fda.usc/man/fregre.igls.Rd fda.usc/man/summary.fregre.fd.Rd fda.usc/man/predict.fregre.scalar.Rd
fda.usc/man/na.omit.rd
fda.usc/man/cond.quantile.Rd fda.usc/man/FDR.Rd fda.usc/man/fdata2pc.Rd fda.usc/man/Var.y.Rd fda.usc/man/fregre.ppls.Rd fda.usc/man/predict.classif.Rd fda.usc/man/tecator.Rd fda.usc/man/fregre.pc.Rd fda.usc/man/min.np.Rd fda.usc/man/classif.tree.Rd fda.usc/man/fregre.gkam.Rd fda.usc/man/fdata.cen.Rd fda.usc/man/Kernel.integrate.Rd fda.usc/man/rp.flm.test.Rd fda.usc/man/Descriptive.Rd fda.usc/man/CV.S.Rd fda.usc/man/DepthMultivariate.Rd fda.usc/man/semimetric.NPFDA.Rd fda.usc/man/anova.hetero.Rd fda.usc/man/DepthFunctional.Rd fda.usc/man/dev.S.Rd fda.usc/man/influence.quan.Rd
fda.usc/man/dcor.test.rd
fda.usc/man/classif.glm.Rd fda.usc/man/cond.mode.Rd fda.usc/man/fdata2fd.Rd fda.usc/man/metric.lp.Rd fda.usc/man/classif.np.Rd fda.usc/man/split_omit.fdata.Rd fda.usc/man/int.simpson.Rd fda.usc/man/flm.test.Rd fda.usc/man/influence.fdata.Rd fda.usc/man/cond.F.Rd fda.usc/man/h.default.Rd fda.usc/man/fdata.methods.Rd fda.usc/man/order.fdata.Rd fda.usc/man/fdata2pls.Rd fda.usc/man/fregre.bootstrap.Rd fda.usc/man/create.fdata.basis.Rd fda.usc/man/fregre.np.Rd fda.usc/man/fregre.basis.Rd fda.usc/man/classif.DD.Rd fda.usc/man/PCvM.statistic.Rd fda.usc/man/predict.classif.DD.Rd fda.usc/man/kmeans.fd.Rd fda.usc/man/summary.fregre.gkam.Rd fda.usc/man/fregre.pc.cv.Rd fda.usc/man/Outliers.fdata.Rd fda.usc/man/flm.Ftest.Rd fda.usc/man/fdata.bootstrap.Rd fda.usc/man/aemet.Rd fda.usc/man/min.basis.Rd fda.usc/man/fdata.deriv.Rd fda.usc/man/predict.fregre.gls.Rd fda.usc/man/fregre.basis.fr.Rd fda.usc/man/fregre.basis.cv.Rd fda.usc/man/gridfdata.Rd fda.usc/man/MCO.Rd fda.usc/man/classif.gkam.Rd fda.usc/man/fregre.plm.Rd fda.usc/man/GCCV.S.Rd fda.usc/man/subset.fdata.Rd fda.usc/man/rwild.Rd fda.usc/man/Kernel.Rd fda.usc/man/S.basis.Rd fda.usc/man/anova.onefactor.Rd fda.usc/man/plot.fdata.Rd fda.usc/man/P.penalty.Rd fda.usc/man/fda.usc-package.Rd fda.usc/man/poblenou.Rd fda.usc/man/norm.fdata.Rd fda.usc/man/summary.classif.Rd fda.usc/man/fdata.Rd fda.usc/man/rproc2fdata.Rd fda.usc/man/GCV.S.Rd fda.usc/man/metric.kl.Rd fda.usc/man/classif.depth.Rd fda.usc/man/rp.flm.statistic.Rd fda.usc/man/semimetric.basis.Rd fda.usc/man/phoneme.Rd fda.usc/man/fregre.glm.Rd fda.usc/man/fregre.lm.Rd fda.usc/man/predict.fregre.fd.Rd fda.usc/man/fregre.np.cv.Rd fda.usc/man/classif.gsam.Rd fda.usc/man/fregre.ppls.cv.Rd fda.usc/man/fregre.pls.cv.Rd fda.usc/man/DepthFunctionalIntegrate.Rd fda.usc/man/inprod.fdata.Rd

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