False Discorvery Rate (FDR)
Delsol, Ferraty and Vieu test for no functional-scalar interaction
Classification Fitting Functional Generalized Additive Models
Depth for a multivariate dataset
Provides the depth measure for multivariate data
The cross-validation (CV) score
Depth for multivariate fdata
Provides the depth measure for a list of p--functional data objects
Detecting outliers for functional dataset
Classifier from Functional Data
Classification Fitting Functional Recursive Partitioning and Regression Trees
Functional Data Analysis and Utilities for Statistical Computing (fda.usc)
Converts raw data or other functional data classes into fdata class.
Asymmetric Smoothing Kernel
Functional ANOVA with Random Project.
Conditional Distribution Function
Compute the Hausdorff distances between two curves.
Cross-validation Functional Regression with scalar response using basis representation.
Create Basis Set for Functional Data of fdata class
PCvM statistic for the Functional Linear Model with scalar response
Proximities between functional data
fdata S3 Group Generic Functions
Smoothing matrix by nonparametric methods.
Smoothing matrix with roughness penalties by basis representation.
Bootstrap samples of a functional statistic
Depth for univariate fdata
Provides the depth measure for functional data
aemet data
Fitting Functional Linear Models
The deviance score .
fda.usc internal functions
Calculation of the smoothing parameter (h) for a functional data
ANOVA for heteroscedastic data
Smoothing of functional data using nonparametric kernel estimation
Fitting Functional Generalized Spectral Additive Models
Utils for generate functional data
Computes the derivative of functional data object.
Goodness-of-fit test for the Functional Linear Model with scalar response using random projections
Bootstrap regression
Mithochondiral calcium overload (MCO) data set
Penalty matrix for higher order differences
Kernel Classifier from Functional Data
Partial least squares components for functional data.
Classification Fitting Functional Generalized Kernel Additive Models
Predicts from a fitted classif object.
F-test for the Functional Linear Model with scalar response
Functional Penalized PLS regression with scalar response
Select the number of basis using GCV method.
Functional Regression with functional response using basis representation.
phoneme data
Functional penalized PC (or PLS) regression with scalar response using selection of number of PC (or PLS) components
Sampling Variance estimates
Fitting Functional Generalized Kernel Additive Models.
Summarizes information from fregre.gkam objects.
Proximities between functional data
Functional Regression with scalar response using basis representation.
Functional penalized PC regression with scalar response using selection of number of PC components
Kullback--Leibler distance
Conditional quantile
Functional regression with scalar response using non-parametric kernel estimation
Summarizes information from fregre.fd objects.
Semi-functional partially linear model with scalar response.
Aproximates Lp-norm for functional data.
Simulate several random processes.
Functional Penalized PC (or PLS) regression with scalar response
Proximities between functional data (semi-metrics)
Aproximates Lp-metric distances for functional data.
Cross-validation functional regression with scalar response using kernel estimation.
Conditional mode
Classification Fitting Functional Generalized Linear Models
Functional Regression with scalar response using Principal Components Analysis.
Descriptive measures for functional data.
The generalized cross-validation (GCV) score.
Predicts from a fitted classif.DD object.
Symmetric Smoothing Kernels.
One--way anova model for functional data
Integrate Smoothing Kernels.
Goodness-of-fit test for the Functional Linear Model with scalar response
Distance Matrix Computation
Principal components for functional data
DD-Classifier Based on DD-plot
Wild bootstrap residuals
predict.functional.response
Predict method for functional response model
Functional penalized PLS regression with scalar response using selection of number of PLS components
Functional data centred (subtract the mean of each discretization point)
Simpson integration
tecator data
Fitting Functional Generalized Linear Models
Statistic for testing the FLM using random projections
poblenou data
Subsetting
Summarizes information from kernel classification methods.
Plot functional data: fdata.
A wrapper for the split and unlist function for fdata object
Functional influence measures
A wrapper for the order Converts fdata class object into fd class object
K-Means Clustering for functional data
Quantile for influence measures
Predict method for functional linear model (fregre.fd class)
Inner products of Functional Data Objects o class (fdata)
Correlation for functional data by Principal Component Analysis
Predict method for functional regression model