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fda.usc (version 1.1.0)

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

Description

The R package fda.usc carries out exploratory and descriptive analysis of functional data such as depth measurements or functional atypical curves detection, functions to compute functional regression models with a scalar response, supervised and unsupervised classification methods and functional analysis of variance.

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Version

Install

install.packages('fda.usc')

Monthly Downloads

2,504

Version

1.1.0

License

GPL-2

Maintainer

Manuel Oviedo de la Fuente

Last Published

December 16th, 2013

Functions in fda.usc (1.1.0)

Smoothing matrix with roughness penalties by basis representation.

Kernel.asymmetric

Asymmetric Smoothing Kernel

Classifier from Functional Data

Fitting Functional Generalized Kernel Additive Models.

Kernel Classifier from Functional Data

Fitting Functional Linear Models

Penalty matrix for higher order differences

False Discorvery Rate (FDR)

Smoothing matrix by nonparametric methods.

Proximities between functional data

Functional regression with scalar response using non-parametric kernel estimation

Computes the derivative of functional data object.

F-test for the Functional Linear Model with scalar response

Converts fdata class object into fd class object

Functional penalized PLS regression with scalar response using selection of number of PLS components

Fitting Functional Generalized Linear Models

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

fregre.ppc,fregre.ppls

Functional Penalized PC (or PLS) regression with scalar response

PCvM statistic for the Functional Linear Model with scalar response

Detecting outliers for functional dataset

fdata S3 Group Generic Functions

Wild bootstrap residuals

Functional data centred (subtract the mean of each discretization point)

Conditional quantile

Classification Fitting Functional Generalized Kernel Additive Models

fda.usc-package

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

Delsol, Ferraty and Vieu test for no functional-scalar interaction

A wrapper for the split and unlist function for functional data

The generalized cross-validation (GCV) score.

Sampling Variance estimates

predict.fregre.fd

Predict method for functional linear model (fregre.fd class)

Functional ANOVA with Random Project.

Classification Fitting Functional Generalized Linear Models

Kullback--Leibler distance

Conditional mode

anova.onefactor

One--way anova model for functional data

Functional penalized PC regression with scalar response using selection of number of PC components

Smoothing of functional data using nonparametric kernel estimation

create.fdata.basis

Create Basis Set for Functional Data of fdata class

Kernel.integrate

Integrate Smoothing Kernels.

Functional penalized PC (or PLS) regression with scalar response using selection of number of PC (or PLS) components

Select the number of basis using GCV method.

Depth Functional

Provides the depth measure for functional data

Functional Penalized PLS regression with scalar response

Descriptive measures for functional and multivariate data.

Depth Multivariate

Provides the depth measure for multivariate data

predict.functional.response

Predict method for functional response model

summary.fregre.gkam

Summarizes information from fregre.gkam objects.

fregre.basis.cv

Cross-validation Functional Regression with scalar response using basis representation.

Cross-validation functional regression with scalar response using kernel estimation.

fdata.bootstrap

Bootstrap samples of a functional statistic

Fitting Functional Generalized Spectral Additive Models

summary.classif

Summarizes information from kernel classification methods.

predict.fregre.GAM

Predict method for functional regression model

Simpson integration

Functional Regression with scalar response using basis representation.

Functional Regression with scalar response using Principal Components Analysis.

summary.fregre.fd

Summarizes information from fregre.fd objects.

semimetric.NPFDA

Proximities between functional data (semi-metrics)

Goodness-of-fit test for the Functional Linear Model with scalar response

Inner products of Functional Data Objects o class (fdata)

Mithochondiral calcium overload (MCO) data set

Symmetric Smoothing Kernels.

The deviance score .

Aproximates Lp-norm for functional data.

Quantile for influence measures

predict.classif

Predicts from a fitted classif object.

Conditional Distribution Function

fda.usc.internal

fda.usc internal functions

Semi-functional partially linear model with scalar response.

fregre.basis.fr

Functional Regression with functional response using basis representation.

Aproximates Lp-metric distances for functional data.

Generate random process of fdata class.

fregre.bootstrap

Bootstrap regression

Plot functional data: fdata.

semimetric.basis

Proximities between functional data

K-Means Clustering for functional data

Classification Fitting Functional Generalized Additive Models

ANOVA for heteroscedastic data

summary.fdata.comp

Correlation for functional data by Principal Component Analysis

Functional influence measures

Distance Matrix Computation

Principal components for functional data

The cross-validation (CV) score

Converts raw data or other functional data classes into fdata class.

Partial least squares components for functional data.

A wrapper for the order function