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 652 downloads 8 exports 1 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK147
source / vignettesOK264
linux-releaseOK135
macos-releaseOK147
macos-oldrelOK185
windows-develOK61
windows-releaseOK50
windows-oldrelOK63
wasm-releaseOK92

Exports:CovCorMPerCovCorPerCrossPeriodogramMCrossPeriodogramMPerACFMPerioRegPerACFPerioReg

Dependencies:MASS