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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>.

Version: 1.0.0
Depends: R (≥ 3.2.2), MASS
Published: 2019-07-23
DOI: 10.32614/CRAN.package.acfMPeriod
Author: Higor Cotta, Valderio Reisen, Pascal Bondon and Céline Lévy-Leduc
Maintainer: Higor Cotta <cotta.higor at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: acfMPeriod results

Documentation:

Reference manual: acfMPeriod.pdf

Downloads:

Package source: acfMPeriod_1.0.0.tar.gz
Windows binaries: r-devel: acfMPeriod_1.0.0.zip, r-release: acfMPeriod_1.0.0.zip, r-oldrel: acfMPeriod_1.0.0.zip
macOS binaries: r-release (arm64): acfMPeriod_1.0.0.tgz, r-oldrel (arm64): acfMPeriod_1.0.0.tgz, r-release (x86_64): acfMPeriod_1.0.0.tgz, r-oldrel (x86_64): acfMPeriod_1.0.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.