CRAN/E | fdaACF

fdaACF

Autocorrelation Function for Functional Time Series

Installation

About

Quantify the serial correlation across lags of a given functional time series using the autocorrelation function and a partial autocorrelation function for functional time series proposed in Mestre et al. (2021) doi:10.1016/j.csda.2020.107108. The autocorrelation functions are based on the L2 norm of the lagged covariance operators of the series. Functions are available for estimating the distribution of the autocorrelation functions under the assumption of strong functional white noise.

Citation fdaACF citation info
github.com/GMestreM/fdaACF
Bug report File report

Key Metrics

Version 1.0.0
R ≥ 3.5.0
Published 2020-10-20 1284 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks fdaACF results

Downloads

Yesterday 12 +9%
Last 7 days 57 +24%
Last 30 days 193 -6%
Last 90 days 586 -30%
Last 365 days 2.887 -26%

Maintainer

Maintainer

Guillermo Mestre Marcos

guillermo.mestre@comillas.edu

Authors

Guillermo Mestre Marcos

aut / cre

José Portela González

aut

Gregory Rice

aut

Antonio Muñoz San Roque

ctb

Estrella Alonso Pérez

ctb

Material

NEWS
Reference manual
Package source

In Views

FunctionalData
TimeSeries

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

fdaACF archive

Depends

R ≥ 3.5.0

Imports

CompQuadForm
pracma
fda
vars

Suggests

testthat
fields