CV.S                    The cross-validation (CV) score
Descriptive             Descriptive measures for functional data.
FDR                     False Discorvery Rate (FDR)
GCCV.S                  The generalized correlated cross-validation
                        (GCCV) score.
GCV.S                   The generalized correlated cross-validation
                        (GCCV) score
Kernel                  Symmetric Smoothing Kernels.
Kernel.asymmetric       Asymmetric Smoothing Kernel
Kernel.integrate        Integrate Smoothing Kernels.
LMDC.select             Impact points selection of functional predictor
                        and regression using local maxima distance
                        correlation (LMDC)
MCO                     Mithochondiral calcium overload (MCO) data set
Outliers.fdata          outliers for functional dataset
P.penalty               Penalty matrix for higher order differences
PCvM.statistic          PCvM statistic for the Functional Linear Model
                        with scalar response
S.basis                 Smoothing matrix with roughness penalties by
                        basis representation.
S.np                    Smoothing matrix by nonparametric methods
Var.y                   Sampling Variance estimates
accuracy                Performance measures for regression and
                        classification models
aemet                   aemet data
classif.DD              DD-Classifier Based on DD-plot
classif.ML              Functional classification using ML algotithms
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.gsam.vs         Variable Selection in Functional Data
                        Classification
classif.kfold           Functional Classification usign k-fold CV
classif.np              Kernel Classifier from Functional Data
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
dcor.xy                 Distance Correlation Statistic and t-Test
depth.fdata             Computation of depth measures for functional
                        data
depth.mdata             Provides the depth measure for multivariate
                        data
depth.mfdata            Provides the depth measure for a list of
                        p-functional data objects
dev.S                   The deviance score
dfv.test                Delsol, Ferraty and Vieu test for no
                        functional-scalar interaction
dis.cos.cor             Proximities between functional data
fEqDistrib.test         Tests for checking the equality of
                        distributions between two functional
                        populations.
fEqMoments.test         Tests for checking the equality of means and/or
                        covariance between two populations under
                        gaussianity.
fanova.RPm              Functional ANOVA with Random Project.
fanova.hetero           ANOVA for heteroscedastic data
fanova.onefactor        One-way anova model for functional data
fda.usc-package         Functional Data Analysis and Utilities for
                        Statistical Computing (fda.usc)
fda.usc.internal        fda.usc internal functions
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.
fdata.methods           fdata S3 Group Generic Functions
fdata2basis             Compute fucntional coefficients from functional
                        data represented in a base of functions
fdata2fd                Converts fdata class object into fd class
                        object
fdata2pc                Principal components for functional data
fdata2pls               Partial least squares components for functional
                        data.
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.glm.vs           Variable Selection using Functional 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
h.default               Calculation of the smoothing parameter (h) for
                        a functional data
influence.fregre.fd     Functional influence measures
influence_quan          Quantile for influence measures
inprod.fdata            Inner products of Functional Data Objects o
                        class (fdata)
int.simpson             Simpson integration
kmeans.center.ini       K-Means Clustering for functional data
ldata                   ldata class definition and utilities
metric.DTW              DTW: Dynamic time warping
metric.dist             Distance Matrix Computation
metric.hausdorff        Compute the Hausdorff distances between two
                        curves.
metric.kl               Kullback-Leibler distance
metric.ldata            Distance Matrix Computation for ldata and
                        mfdata class object
metric.lp               Approximates Lp-metric distances for functional
                        data.
mfdata                  mfdata class definition and utilities
na.omit.fdata           A wrapper for the na.omit and na.fail function
                        for fdata object
norm.fdata              Approximates Lp-norm for functional data.
ops.fda.usc             ops.fda.usc Options Settings
optim.basis             Select the number of basis using GCV method.
optim.np                Smoothing of functional data using
                        nonparametric kernel estimation
phoneme                 phoneme data
plot.fdata              Plot functional data: fdata class object
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 linear model
predict.fregre.gls      Predictions from a functional gls object
r.ou                    Ornstein-Uhlenbeck process
rcombfdata              Utils for generate functional data
rdir.pc                 Data-driven sampling of random directions
                        guided by sample of functional data
rp.flm.statistic        Statistics for testing the functional linear
                        model using random projections
rp.flm.test             Goodness-of fit test for the functional linear
                        model using random projections
rproc2fdata             Simulate several random processes.
rwild                   Wild bootstrap residuals
semimetric.NPFDA        Proximities between functional data
                        (semi-metrics)
semimetric.basis        Proximities between functional data
subset.fdata            Subsetting
summary.classif         Summarizes information from kernel
                        classification methods.
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.
tecator                 tecator data
weights4class           Weighting tools
