Package: acfMPeriod 1.0.0

acfMPeriod: Robust Estimation of the ACF from the M-Periodogram

Non-robust and robust computations of the sample autocovariance (ACOVF) and sample autocorrelation functions (ACF) of univariate and multivariate processes. The methodology consists in reversing the diagonalization procedure involving the periodogram or the cross-periodogram and the Fourier transform vectors, and, thus, obtaining the ACOVF or the ACF as discussed in Fuller (1995) <doi:10.1002/9780470316917>. The robust version is obtained by fitting robust M-regressors to obtain the M-periodogram or M-cross-periodogram as discussed in Reisen et al. (2017) <doi:10.1016/j.jspi.2017.02.008>.

Authors:Higor Cotta, Valderio Reisen, Pascal Bondon and Céline Lévy-Leduc

acfMPeriod_1.0.0.tar.gz
acfMPeriod_1.0.0.zip(r-4.7-any)acfMPeriod_1.0.0.zip(r-4.6-any)acfMPeriod_1.0.0.zip(r-4.5-any)
acfMPeriod_1.0.0.tgz(r-4.6-any)acfMPeriod_1.0.0.tgz(r-4.5-any)
acfMPeriod_1.0.0.tar.gz(r-4.7-any)acfMPeriod_1.0.0.tar.gz(r-4.6-any)
acfMPeriod_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
acfMPeriod/json (API)

# Install 'acfMPeriod' in R:
install.packages('acfMPeriod', repos = c('https://rogih.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/rogih/acfmperiod/issues

On CRAN:

Conda:

2.00 score 4 scripts 571 downloads 8 exports 1 dependencies

Last updated from:72e44abae8. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK99
source / vignettesOK130
linux-release-x86_64OK91
macos-release-arm64OK120
macos-oldrel-arm64OK126
windows-develOK67
windows-releaseOK53
windows-oldrelOK65
wasm-releaseOK94

Exports:CovCorMPerCovCorPerCrossPeriodogramMCrossPeriodogramMPerACFMPerioRegPerACFPerioReg

Dependencies:MASS