Functional Data Analysis and Utilities for Statistical Computing

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Documentation for package ‘fda.usc’ version 1.5.0

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A B C D F G H I K L M N O P Q R S T U V misc

fda.usc-package Functional Data Analysis and Utilities for Statistical Computing (fda.usc)

-- A --

Adot PCvM statistic for the Functional Linear Model with scalar response
aemet aemet data
AKer.cos Asymmetric Smoothing Kernel
AKer.epa Asymmetric Smoothing Kernel
AKer.norm Asymmetric Smoothing Kernel
AKer.quar Asymmetric Smoothing Kernel
AKer.tri Asymmetric Smoothing Kernel
AKer.unif Asymmetric Smoothing Kernel
anova.hetero ANOVA for heteroscedastic data
anova.onefactor One-way anova model for functional data
anova.RPm Functional ANOVA with Random Project.
anova.RPm.boot Functional ANOVA with Random Project.
anyNA.fdata fda.usc internal functions
argvals fda.usc internal functions

-- B --

bcdcor.dist Distance Correlation Statistic and t-Test

-- C --

c.fdata fda.usc internal functions
classif.DD DD-Classifier Based on DD-plot
classif.depth Classifier from Functional Data
classif.gkam Classification Fitting Functional Generalized Kernel Additive Models
classif.glm Classification Fitting Functional Generalized Linear Models
classif.gsam Classification Fitting Functional Generalized Additive Models
classif.kernel Kernel Classifier from Functional Data
classif.knn Kernel Classifier from Functional Data
classif.np Kernel Classifier from Functional Data
classif.tree Classification Fitting Functional Recursive Partitioning and Regression Trees
colnames.fdata fda.usc internal functions
cond.F Conditional Distribution Function
cond.mode Conditional mode
cond.quantile Conditional quantile
count.na.fdata fda.usc internal functions
create.fdata.basis Create Basis Set for Functional Data of fdata class
create.pc.basis Create Basis Set for Functional Data of fdata class
create.pls.basis Create Basis Set for Functional Data of fdata class
create.raw.fdata Create Basis Set for Functional Data of fdata class
CV.S The cross-validation (CV) score

-- D --

dcor.dist Distance Correlation Statistic and t-Test
dcor.test Distance Correlation Statistic and t-Test
dcor.xy Distance Correlation Statistic and t-Test
Depth Computation of depth measures for functional data
depth.FM Computation of depth measures for functional data
depth.FMp Provides the depth measure for a list of p-functional data objects
depth.FSD Computation of depth measures for functional data
depth.KFSD Computation of depth measures for functional data
depth.mode Computation of depth measures for functional data
depth.modep Provides the depth measure for a list of p-functional data objects
Depth.Multivariate Provides the depth measure for multivariate data
Depth.pfdata Provides the depth measure for a list of p-functional data objects
depth.RP Computation of depth measures for functional data
depth.RPD Computation of depth measures for functional data
depth.RPp Provides the depth measure for a list of p-functional data objects
depth.RT Computation of depth measures for functional data
Descriptive Descriptive measures for functional data.
dev.S The deviance score .
dfv.statistic Delsol, Ferraty and Vieu test for no functional-scalar interaction
dfv.test Delsol, Ferraty and Vieu test for no functional-scalar interaction
dim.fdata fda.usc internal functions
dis.cos.cor Proximities between functional data

-- F --

fda.usc Functional Data Analysis and Utilities for Statistical Computing (fda.usc)
fdata Converts raw data or other functional data classes into fdata class.
fdata.bootstrap Bootstrap samples of a functional statistic
fdata.cen Functional data centred (subtract the mean of each discretization point)
fdata.deriv Computes the derivative of functional data object.
fdata2fd Converts fdata class object into fd class object
fdata2pc Principal components for functional data
fdata2pls Partial least squares components for functional data.
fdata2ppc Principal components for functional data
fdata2ppls Partial least squares components for functional data.
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 scalar response
fregre.basis Functional Regression with scalar response using basis representation.
fregre.basis.cv Cross-validation Functional Regression with scalar response using basis representation.
fregre.basis.fr Functional Regression with functional response using basis representation.
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.gsam.vs Variable Selection using Functional 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 non-parametric kernel estimation
fregre.np.cv Cross-validation functional regression with scalar response using kernel estimation.
fregre.pc Functional Regression with scalar response using Principal Components Analysis.
fregre.pc.cv Functional penalized PC regression with scalar response using selection of number of PC components
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 using selection of number of PLS components
fregre.ppc Functional Penalized PC (or PLS) regression with scalar response
fregre.ppc.cv Functional penalized PC (or PLS) regression with scalar response using selection of number of PC (or PLS) components
fregre.ppls Functional Penalized PC (or PLS) regression with scalar response
fregre.ppls.cv Functional penalized PC (or PLS) regression with scalar response using selection of number of PC (or PLS) components
Ftest.statistic F-test for the Functional Linear Model with scalar response
func.mean Descriptive measures for functional data.
func.mean.formula Descriptive measures for functional data.
func.med.FM Descriptive measures for functional data.
func.med.mode Descriptive measures for functional data.
func.med.RP Descriptive measures for functional data.
func.med.RPD Descriptive measures for functional data.
func.med.RT Descriptive measures for functional data.
func.trim.FM Descriptive measures for functional data.
func.trim.mode Descriptive measures for functional data.
func.trim.RP Descriptive measures for functional data.
func.trim.RPD Descriptive measures for functional data.
func.trim.RT Descriptive measures for functional data.
func.trimvar.FM Descriptive measures for functional data.
func.trimvar.mode Descriptive measures for functional data.
func.trimvar.RP Descriptive measures for functional data.
func.trimvar.RPD Descriptive measures for functional data.
func.trimvar.RT Descriptive measures for functional data.
func.var Descriptive measures for functional data.

-- G --

GCCV.S The generalized correlated cross-validation (GCCV) score.
GCV.S The generalized cross-validation (GCV) score.
gridfdata Utils for generate functional data

-- H --

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

-- I --

IKer.cos Integrate Smoothing Kernels.
IKer.epa Integrate Smoothing Kernels.
IKer.norm Integrate Smoothing Kernels.
IKer.quar Integrate Smoothing Kernels.
IKer.tri Integrate Smoothing Kernels.
IKer.unif Integrate Smoothing Kernels.
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
is.fdata fda.usc internal functions
is.na.fdata fda.usc internal functions

-- K --

Ker.cos Symmetric Smoothing Kernels.
Ker.epa Symmetric Smoothing Kernels.
Ker.norm Symmetric Smoothing Kernels.
Ker.quar Symmetric Smoothing Kernels.
Ker.tri Symmetric Smoothing Kernels.
Ker.unif Symmetric Smoothing Kernels.
Kernel Symmetric Smoothing Kernels.
Kernel.asymmetric Asymmetric Smoothing Kernel
Kernel.integrate Integrate Smoothing Kernels.
kgam.H Fitting Functional Generalized Kernel Additive Models.
kmeans.assig.groups K-Means Clustering for functional data
kmeans.center.ini K-Means Clustering for functional data
kmeans.centers.update K-Means Clustering for functional data
kmeans.fd K-Means Clustering for functional data

-- L --

length.fdata fda.usc internal functions
lines.fdata Plot functional data: fdata.
LMDC.regre Impact points selection of functional predictor and regression using local maxima distance correlation (LMDC)
LMDC.select Impact points selection of functional predictor and regression using local maxima distance correlation (LMDC)

-- M --

Math.fdata fdata S3 Group Generic Functions
MCO Mithochondiral calcium overload (MCO) data set
mdepth.HS Provides the depth measure for multivariate data
mdepth.LD Provides the depth measure for multivariate data
mdepth.MhD Provides the depth measure for multivariate data
mdepth.RP Provides the depth measure for multivariate data
mdepth.SD Provides the depth measure for multivariate data
mdepth.TD Provides the depth measure for multivariate data
metric.dist Distance Matrix Computation
metric.hausdorff Compute the Hausdorff distances between two curves.
metric.kl Kullback-Leibler distance
metric.lp Approximates 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 estimation
missing.fdata fda.usc internal functions

-- N --

na.fail.fdata A wrapper for the na.omit and na.fail function for fdata object
na.omit.fdata A wrapper for the na.omit and na.fail function for fdata object
NCOL.fdata fda.usc internal functions
ncol.fdata fda.usc internal functions
norm.fd Approximates Lp-norm for functional data.
norm.fdata Approximates Lp-norm for functional data.
NROW.fdata fda.usc internal functions
nrow.fdata fda.usc internal functions

-- O --

omit.fdata fda.usc internal functions
omit2.fdata fda.usc internal functions
Ops.fdata fdata S3 Group Generic Functions
order.fdata A wrapper for the 'order' function
outliers.depth.pond Detecting outliers for functional dataset
outliers.depth.trim Detecting outliers for functional dataset
Outliers.fdata Detecting outliers for functional dataset
outliers.lrt Detecting outliers for functional dataset
outliers.thres.lrt Detecting outliers for functional dataset

-- P --

P.penalty Penalty matrix for higher order differences
PCvM.statistic PCvM statistic for the Functional Linear Model with scalar response
phoneme phoneme data
plot.bifd Plot functional data: fdata.
plot.depth Plot functional data: fdata.
plot.fdata Plot functional data: fdata.
plot.mdepth Plot functional data: fdata.
plot.summary.lm Summarizes information from fregre.fd objects.
poblenou poblenou data
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.fr Predict method for functional response model
predict.fregre.gkam Predict method for functional regression model
predict.fregre.glm Predict method for functional regression model
predict.fregre.gls Predictions from a functional gls object
predict.fregre.gsam Predict method for functional regression model
predict.fregre.igls Predictions from a functional gls object
predict.fregre.lm Predict method for functional regression model
predict.fregre.plm Predict method for functional regression model
print.classif Summarizes information from kernel classification methods.
print.fregre.fd Summarizes information from fregre.fd objects.
print.fregre.gkam Summarizes information from fregre.gkam objects.
pvalue.FDR False Discorvery Rate (FDR)

-- Q --

quantile.outliers.pond Detecting outliers for functional dataset
quantile.outliers.trim Detecting outliers for functional dataset

-- R --

r.ou Ornstein-Uhlenbeck process
rangeval fda.usc internal functions
rcombfdata Utils for generate functional data
rdir.pc Data-driven sampling of random directions guided by sample of functional data
rownames.fdata fda.usc internal functions
rp.flm.statistic Statistic for testing the FLM using random projections
rp.flm.test Goodness-of-fit test for the Functional Linear Model with scalar response using random projections
rproc2fdata Simulate several random processes.
rwild Wild bootstrap residuals

-- S --

S.basis Smoothing matrix with roughness penalties by basis representation.
S.KNN Smoothing matrix by nonparametric methods.
S.LLR Smoothing matrix by nonparametric methods.
S.np Smoothing matrix by nonparametric methods.
S.NW Smoothing matrix by nonparametric methods.
semimetric.basis Proximities between functional data
semimetric.deriv Proximities between functional data (semi-metrics)
semimetric.fourier Proximities between functional data (semi-metrics)
semimetric.hshift Proximities between functional data (semi-metrics)
semimetric.mplsr Proximities between functional data (semi-metrics)
semimetric.NPFDA Proximities between functional data (semi-metrics)
semimetric.pca Proximities between functional data (semi-metrics)
split.fdata A wrapper for the split and unlist function for fdata object
subset.fdata Subsetting
summary.anova Functional ANOVA with Random Project.
summary.classif Summarizes information from kernel classification methods.
Summary.fdata fdata S3 Group Generic Functions
summary.fdata.comp Correlation for functional data by Principal Component Analysis
summary.fregre.fd Summarizes information from fregre.fd objects.
summary.fregre.gkam Summarizes information from fregre.gkam objects.
summary.fregre.lm Summarizes information from fregre.fd objects.

-- T --

tecator tecator data
title.fdata Plot functional data: fdata.

-- U --

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

-- V --

Var.e Sampling Variance estimates
Var.y Sampling Variance estimates

-- misc --

!=.fdata fda.usc internal functions
*.fdata fda.usc internal functions
+.fdata fda.usc internal functions
-.fdata fda.usc internal functions
/.fdata fda.usc internal functions
==.fdata fda.usc internal functions
[.fdata fda.usc internal functions
[.fdist fda.usc internal functions
^.fdata fda.usc internal functions