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

[Up] [Top]

Documentation for package ‘fda.usc’ version 0.9.5

Help Pages

A C D F G H I K L M N O P Q R S T V misc

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

-- A --

aemet aemet data
AKer.cos Asymmetric Smoothing Kernel
AKer.epa Asymmetric Smoothing Kernel
AKer.norm Asymmetric Smoothing Kernel
AKer.quar Asymmetric Smoothing Kernel
AKer.tri Asymmetric Smoothing Kernel
AKer.unif Asymmetric Smoothing Kernel
anova.hetero ANOVA for heteroscedastic data
anova.RPm Functional ANOVA with Random Project.
anova.RPm.boot Functional ANOVA with Random Project.

-- C --

c.fdata fda.usc internal functions
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
count.na fda.usc internal functions
create.fdata.basis Create Basis Set for Functional Data of fdata class
create.pc.basis Create Basis Set for Functional Data of fdata class
CV.S The cross-validation (CV) score

-- D --

Depth Provides the depth measure for functional data
depth.FM Fraiman-Muniz depth measure
depth.mode Provides the depth measure (mode) for functional data
depth.RP Provides the depth measure using random projections for functional data
depth.RPD Provides the depth measure by random projections using derivatives
Descriptive Descriptive measures for functional data.
dim.fdata fda.usc internal functions

-- F --

fda.usc 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
FDR False Discorvery Rate (FDR)
fregre.basis Functional Regression with scalar response using basis representation.
fregre.basis.cv Cross-validation Functional Regression with scalar response using basis representation.
fregre.combn Functional Regression using selection of number of principal components
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
func.mean Descriptive measures for functional data.
func.med.FM Descriptive measures for functional data.
func.med.mode Descriptive measures for functional data.
func.med.RP Descriptive measures for functional data.
func.med.RPD Descriptive measures for functional data.
func.trim.FM Descriptive measures for functional data.
func.trim.mode Descriptive measures for functional data.
func.trim.RP Descriptive measures for functional data.
func.trim.RPD Descriptive measures for functional data.
func.trimvar.FM Descriptive measures for functional data.
func.trimvar.mode Descriptive measures for functional data.
func.trimvar.RP Descriptive measures for functional data.
func.trimvar.RPD Descriptive measures for functional data.
func.var Descriptive measures for functional data.

-- G --

GCV.S The generalized cross-validation (GCV) score.

-- H --

h.default Calculation of the smoothing parameter (h) for a functional data
hshift Proximities between functional data (semi-metrics)

-- I --

IKer.cos Integrate Smoothing Kernels.
IKer.epa Integrate Smoothing Kernels.
IKer.norm Integrate Smoothing Kernels.
IKer.quar Integrate Smoothing Kernels.
IKer.tri Integrate Smoothing Kernels.
IKer.unif Integrate Smoothing Kernels.
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
int.simpson2 Simpson integration
intercambio Functional ANOVA with Random Project.
intercambio.l Functional ANOVA with Random Project.
is.fdata fda.usc internal functions

-- K --

Ker.cos Symmetric Smoothing Kernels.
Ker.epa Symmetric Smoothing Kernels.
Ker.norm Symmetric Smoothing Kernels.
Ker.quar Symmetric Smoothing Kernels.
Ker.tri Symmetric Smoothing Kernels.
Ker.unif Symmetric Smoothing Kernels.
Kernel Symmetric Smoothing Kernels.
Kernel.asymmetric Asymmetric Smoothing Kernel
Kernel.integrate Integrate Smoothing Kernels.
kmeans.assig.groups K-Means Clustering for functional data
kmeans.center.ini K-Means Clustering for functional data
kmeans.centers.update K-Means Clustering for functional data
kmeans.fd K-Means Clustering for functional data

-- L --

lines.fdata Plot functional data: fdata.

-- M --

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
mplsr Proximities between functional data (semi-metrics)

-- N --

ncol.fdata fda.usc internal functions
norm.fd Aproximates Lp-norm for functional data.
norm.fdata Aproximates Lp-norm for functional data.
nrow.fdata fda.usc internal functions

-- O --

outliers.depth.pond Detecting outliers for functional dataset
outliers.depth.trim Detecting outliers for functional dataset
Outliers.fdata Detecting outliers for functional dataset
outliers.lrt Detecting outliers for functional dataset
outliers.thres.lrt Detecting outliers for functional dataset

-- P --

pc.cor Correlation for functional data by Principal Component Analysis
pc.fdata Principal components for functional data
pc.svd.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.
print.classif.fd Summarizes information from kernel classification methods.
print.fregre.fd Summarizes information from fregre.fd objects.
pvalue.FDR False Discorvery Rate (FDR)

-- Q --

quantile.outliers.pond Detecting outliers for functional dataset
quantile.outliers.trim Detecting outliers for functional dataset

-- R --

rkernel Symmetric Smoothing Kernels.

-- S --

S.basis Smoothing matrix with roughness penalties by basis representation.
S.KNN Smoothing matrix by nonparametric methods.
S.LLR Smoothing matrix by nonparametric methods.
S.np Smoothing matrix by nonparametric methods.
S.NW Smoothing matrix by nonparametric methods.
semimetric.basis Proximities between functional data
semimetric.deriv Proximities between functional data (semi-metrics)
semimetric.fourier Proximities between functional data (semi-metrics)
semimetric.hshift Proximities between functional data (semi-metrics)
semimetric.mplsr Proximities between functional data (semi-metrics)
semimetric.NPFDA Proximities between functional data (semi-metrics)
semimetric.pca Proximities between functional data (semi-metrics)
summary.anova Functional ANOVA with Random Project.
summary.classif.fd Summarizes information from kernel classification methods.
summary.fregre.fd Summarizes information from fregre.fd objects.

-- T --

tecator tecator data
title.fdata Plot functional data: fdata.
traza fda.usc internal functions

-- V --

Var.e Sampling Variance estimates
Var.y Sampling Variance estimates

-- misc --

*.fdata fda.usc internal functions
+.fdata fda.usc internal functions
-.fdata fda.usc internal functions
/.fdata fda.usc internal functions
==.fdata fda.usc internal functions
[.fdata fda.usc internal functions
^.fdata fda.usc internal functions