The cross-validation (CV) score
Integrate Smoothing Kernels.
Asymmetric Smoothing Kernel
Sampling Variance estimates
Smoothing matrix by nonparametric methods
Descriptive measures for functional data.
Proximities between functional data
Functional ANOVA with Random Project.
Converts fdata class object into fd class object
Impact points selection of functional predictor and regression using local
maxima distance correlation (LMDC)
Kernel Classifier from Functional Data
Functional Classification usign k-fold CV
fdata S3 Group Generic Functions
Performance measures for regression and classification models
The generalized correlated cross-validation (GCCV) score
Symmetric Smoothing Kernels.
DD-Classifier Based on DD-plot
Mithochondiral calcium overload (MCO) data set
False Discorvery Rate (FDR)
PCvM statistic for the Functional Linear Model with scalar response
Classifier from Functional Data
Fitting Functional Generalized Linear Models
Smoothing matrix with roughness penalties by basis representation.
Fitting Functional Generalized Kernel Additive Models.
Functional classification using ML algotithms
Conditional Distribution Function
Classification Fitting Functional Generalized Kernel Additive Models
Conditional quantile
aemet data
Conditional mode
Create Basis Set for Functional Data of fdata class
Distance Correlation Statistic and t-Test
Functional Data Analysis and Utilities for Statistical Computing (fda.usc)
Computation of depth measures for functional data
The deviance score
Provides the depth measure for multivariate data
Functional Penalized PLS regression with scalar response
Delsol, Ferraty and Vieu test for no functional-scalar interaction
Provides the depth measure for a list of p--functional data objects
Partial least squares components for functional data.
The generalized correlated cross-validation (GCCV) score.
Principal components for functional data
fda.usc internal functions
Fitting Functional Linear Models
Functional Regression with scalar response using basis representation.
Functional Regression with functional response using basis representation.
Bootstrap regression
outliers for functional dataset
Cross-validation Functional Regression with scalar response using basis
representation.
Functional regression with scalar response using non-parametric kernel
estimation
Distance Matrix Computation
Calculation of the smoothing parameter (h) for a functional data
phoneme data
Functional influence measures
Functional data centred (subtract the mean of each discretization point)
Functional penalized PLS regression with scalar response using selection of
number of PLS components
Penalty matrix for higher order differences
Plot functional data: fdata class object
Compute the Hausdorff distances between two curves.
Functional penalized PC regression with scalar response using selection of
number of PC components
ldata class definition and utilities
Semi-functional partially linear model with scalar response.
Fit Functional Linear Model Using Generalized Least Squares
Computes the derivative of functional data object.
Fitting Functional Generalized Spectral Additive Models
Fit of Functional Generalized Least Squares Model Iteratively
Variable Selection using Functional Additive Models
Data-driven sampling of random directions guided by sample of functional
data
poblenou data
Approximates Lp-metric distances for functional data.
Predicts from a fitted classif.DD object.
DTW: Dynamic time warping
Predict method for functional linear model
A wrapper for the na.omit and na.fail function for fdata object
Classification Fitting Functional Generalized Linear Models
Subsetting
Ornstein-Uhlenbeck process
Correlation for functional data by Principal Component Analysis
Kullback--Leibler distance
Goodness-of fit test for the functional linear model using random
projections
Classification Fitting Functional Generalized Additive Models
Statistics for testing the functional linear model using random projections
Distance Matrix Computation for ldata and mfdata class object
Utils for generate functional data
Summarizes information from kernel classification methods.
Summarizes information from fregre.fd objects.
ANOVA for heteroscedastic data
One--way anova model for functional data
Simpson integration
Bootstrap samples of a functional statistic
ops.fda.usc Options Settings
Goodness-of-fit test for the Functional Linear Model with scalar response
K-Means Clustering for functional data
Predict method for functional response model
Approximates Lp-norm for functional data.
F-test for the Functional Linear Model with scalar response
Summarizes information from fregre.gkam objects.
tecator data
Converts raw data or other functional data classes into fdata class.
Proximities between functional data
Cross-validation functional regression with scalar response using kernel
estimation.
Proximities between functional data (semi-metrics)
Predictions from a functional gls object
Functional Regression with scalar response using Principal Components
Analysis
Inner products of Functional Data Objects o class (fdata)
Quantile for influence measures
Predict method for functional linear model (fregre.fd class)
Select the number of basis using GCV method.
Wild bootstrap residuals
Smoothing of functional data using nonparametric kernel estimation
Weighting tools
Predicts from a fitted classif object.
Simulate several random processes.