CV.S                    The cross-validation (CV) score
Depth                   Provides the depth measure for functional data
Descriptive             Descriptive measures for functional data.
FDR                     False Discorvery Rate (FDR)
GCV.S                   The generalized cross-validation (GCV) score.
Kernel                  Symmetric Smoothing Kernels.
Kernel.asymmetric       Asymmetric Smoothing Kernel
Kernel.integrate        Integrate Smoothing Kernels.
Outliers.fdata          Detecting outliers for functional dataset
S.basis                 Smoothing matrix with roughness penalties by
                        basis representation.
S.np                    Smoothing matrix by nonparametric methods.
Var.y                   Sampling Variance estimates
[.fdata                 fda.usc internal functions
aemet                   aemet data
anova.RPm               Functional ANOVA with Random Project.
anova.hetero            ANOVA for heteroscedastic data
classif.kernel.fb       Kernel classifier from Functional Data Training
                        by basis representation
classif.kernel.fd       Kernel Classifier from Functional Data
classif.knn.fd          k-Nearest Neighbor 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
depth.FM                Fraiman-Muniz depth measure
depth.RP                Provides the depth measure using random
                        projections for functional data
depth.RPD               Provides the depth measure by random
                        projections using derivatives
depth.mode              Provides the depth measure (mode) for
                        functional data
fda.usc-package         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
fregre.basis            Functional Regression with scalar response
                        using basis representation.
fregre.basis.cv         Cross-validation Functional Regression with
                        scalar response using basis representation.
fregre.glm              Fitting Functional Generalized Linear Models
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 Regression using selection of number
                        of principal components
fregre.plm              Semi-functional linear regression with scalar
                        response.
fregre.pls              Functional PLS regression with scalar response
fregre.pls.cv           Functional 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.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
kmeans.fd               K-Means Clustering for functional data
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 estimation
norm.fdata              Aproximates Lp-norm for functional data.
pc.cor                  Correlation for functional data by Principal
                        Component Analysis
pc.fdata                Principal components for functional data
phoneme                 phoneme data
plot.fdata              Plot functional data: fdata.
pls.fdata               Partial least squares components for functional
                        data.
poblenou                poblenou data
predict.classif.fd      Predicts from a fitted classif.fd object.
predict.fregre.fd       Predict method for functional linear model
                        (fregre.fd class)
predict.fregre.glm      Predict method for functional linear model of
                        fregre.glm fits object
predict.fregre.lm       Predict method for functional linear model of
                        fregre.lm fits object
predict.fregre.plm      Predict method for semi-functional linear
                        regression model.
semimetric.NPFDA        Proximities between functional data
                        (semi-metrics)
semimetric.basis        Proximities between functional data
summary.classif.fd      Summarizes information from kernel
                        classification methods.
summary.fregre.fd       Summarizes information from fregre.fd objects.
tecator                 tecator data
