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)acfMPeriod_1.0.0.zip(r-4.6)acfMPeriod_1.0.0.zip(r-4.5)
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
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 3 scripts 616 downloads 8 exports 1 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK107
source / vignettesOK148
linux-release-x86_64OK103
macos-release-arm64OK123
macos-oldrel-arm64OK147
windows-develOK68
windows-releaseOK63
windows-oldrelOK90
wasm-releaseOK91

Exports:CovCorMPerCovCorPerCrossPeriodogramMCrossPeriodogramMPerACFMPerioRegPerACFPerioReg

Dependencies:MASS