Learn R Programming

⚠️There's a newer version (0.6-7) of this package.Take me there.

far

R package for modelization of Functional AutoRegressive processes

In collaboration with Serge Guillas, I write a paper called Estimation and simulation of autoregressive Hilbertian processes with exogenous variables which introduced application of ARH models, also known as FAR (Functional AutoRegressive processes).

We write this library during this work and decided to freely distribute it as this work is now finished.

This library include modelizations and previsions functions for Functional AutoRegressive processes using nonparametric methods: functional kernel,estimation of the covariance operator in a subspace, ...

Copy Link

Version

Install

install.packages('far')

Monthly Downloads

401

Version

0.6-5

License

LGPL-2.1

Issues

Pull Requests

Stars

Forks

Maintainer

Damon Julien Guillas Serge

Last Published

July 20th, 2015

Functions in far (0.6-5)

far

FARX(1) model estimation
coef.far

Extract Model Coefficients
interpol.matrix

Interpolation matrix
simul.far.wiener

FAR(1) process simulation with Wiener noise
is.na.fdata

Not Available / ``Missing'' Values
predict.kerfon

Forecasting of functional kernel model
orthonormalization

Orthonormalization of a set of a matrix
base.simul.far

Creating functional basis
simul.far

FAR(1) process simulation
plot.fdata

Plot Functional Data
simul.farx

FARX(1) process simulation
invgen

Generalized inverse of a Matrix
select.fdata

Subscript of fdata
simul.far.sde

FAR-SDE process simulation
fdata

Functional Data class
maxfdata

Maxima of functional data
BaseK2BaseC

Changing Basis
kerfon

Functional Kernel estimation
pred.persist

Forecasting using functional persistence
simul.wiener

Wiener process simulation
far.cv

Cross Validation for FARX(1) model
date.fdata

Extract the date of fdata
multplot

Multivariate plots
predict.far

Forecasting of FARX(1) model
fapply

Apply functions over a fdata object