mvDFA: Multivariate Detrended Fluctuation Analysis

Package: mvDFA 0.0.4

Julien Patrick Irmer

mvDFA: Multivariate Detrended Fluctuation Analysis

This R package provides an implementation of multivariate extensions of a well-known fractal analysis technique, Detrended Fluctuations Analysis (DFA; Peng et al., 1995<doi:10.1063/1.166141>), for multivariate time series: multivariate DFA (mvDFA). Several coefficients are implemented that take into account the correlation structure of the multivariate time series to varying degrees. These coefficients may be used to analyze long memory and changes in the dynamic structure that would by univariate DFA. Therefore, this R package aims to extend and complement the original univariate DFA (Peng et al., 1995) for estimating the scaling properties of nonstationary time series.

Authors:Julien Patrick Irmer [aut, cre, cph], Sebastian Wallot [aut, ctb]

mvDFA_0.0.4.tar.gz
mvDFA_0.0.4.zip(r-4.7-any)mvDFA_0.0.4.zip(r-4.6-any)mvDFA_0.0.4.zip(r-4.5-any)
mvDFA_0.0.4.tgz(r-4.6-any)mvDFA_0.0.4.tgz(r-4.5-any)
mvDFA_0.0.4.tar.gz(r-4.7-any)mvDFA_0.0.4.tar.gz(r-4.6-any)
mvDFA_0.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mvDFA/json (API)

# Install 'mvDFA' in R:

install.packages('mvDFA', repos = c('https://jpirmer.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jpirmer/mvdfa/issues

On CRAN:

3.70 score 1 stars 3 scripts 255 downloads 5 exports 18 dependencies

Last updated from:00e19fa6d8. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	110
source / vignettes	OK	139
linux-release	OK	120
macos-release	OK	195
macos-oldrel	OK	184
windows-devel	OK	93
windows-release	OK	80
windows-oldrel	OK	79
wasm-release	OK	88

Exports:DFA mvDFA simulate_cMTS simulate_Lorenz_noise simulate_MTS_mixed_white_pink_brown

Dependencies:BB DEoptimR deSolve lattice longmemo MASS Matrix MatrixModels mvtnorm pbapply pracma quadprog quantreg rgenoud RobPer robustbase SparseM survival

mvDFA

Install the package | Install the latest working version from GitHub | Test functions for approximated correlated Time Series with different Hurst Exponent | Simulate correlated time series | Estimate multivariate extensions of Hurst exponent for correlated time series | References

Rendered frommvDFA.Rmdusingknitr::rmarkdown

Help page	Topics
Analyze univariate time series and estimate long memory using Detrended Fluctuations Analysis (DFA; Peng et al., 1995)	DFA
Analyze multivariate correlated time series and estimate long memory by the extension of the using univariate Detrended Fluctuations Analysis (DFA; Peng et al., 1995) to multivariate time series: mvDFA	mvDFA
print object of class DFA	print.DFA
print object of class mvDFA	print.mvDFA
Approximate correlated time series with given Hurst Exponent	simulate_cMTS
Simulate the Lorenz System with noise	simulate_Lorenz_noise
Approximate correlated time series from white, pink and brown noise from independent realization of normal variables	simulate_MTS_mixed_white_pink_brown

Help page

Topics

Analyze univariate time series and estimate long memory using Detrended Fluctuations Analysis (DFA; Peng et al., 1995)

DFA

Analyze multivariate correlated time series and estimate long memory by the extension of the using univariate Detrended Fluctuations Analysis (DFA; Peng et al., 1995) to multivariate time series: mvDFA

mvDFA

print object of class DFA

print.DFA

print object of class mvDFA

print.mvDFA

Approximate correlated time series with given Hurst Exponent

simulate_cMTS