fitHeavyTail: Mean and Covariance Matrix Estimation under Heavy Tails

Robust estimation methods for the mean vector, scatter matrix, and covariance matrix (if it exists) from data (possibly containing NAs) under multivariate heavy-tailed distributions such as angular Gaussian (via Tyler's method), Cauchy, and Student's t distributions. Additionally, a factor model structure can be specified for the covariance matrix. The latest revision also includes the multivariate skewed t distribution. The package is based on the papers: Sun, Babu, and Palomar (2014); Sun, Babu, and Palomar (2015); Liu and Rubin (1995); Zhou, Liu, Kumar, and Palomar (2019); Pascal, Ollila, and Palomar (2021).

Version: 0.2.0
Imports: ICSNP, mvtnorm, ghyp, numDeriv, stats
Suggests: ggplot2, reshape2, knitr, rmarkdown, R.rsp, testthat
Published: 2023-05-01
DOI: 10.32614/CRAN.package.fitHeavyTail
Author: Daniel P. Palomar [cre, aut], Rui Zhou [aut], Xiwen Wang [aut], Frédéric Pascal [ctb], Esa Ollila [ctb]
Maintainer: Daniel P. Palomar <daniel.p.palomar at gmail.com>
BugReports: https://github.com/convexfi/fitHeavyTail/issues
License: GPL-3
URL: https://CRAN.R-project.org/package=fitHeavyTail, https://github.com/convexfi/fitHeavyTail, https://www.danielppalomar.com, https://doi.org/10.1109/TSP.2014.2348944, https://doi.org/10.1109/TSP.2015.2417513, https://doi.org/10.23919/EUSIPCO54536.2021.9616162
NeedsCompilation: no
Citation: fitHeavyTail citation info
Materials: README NEWS
CRAN checks: fitHeavyTail results

Documentation:

Reference manual: fitHeavyTail.pdf
Vignettes: Mean Vector and Covariance Matrix Estimation under Heavy Tails

Downloads:

Package source: fitHeavyTail_0.2.0.tar.gz
Windows binaries: r-devel: fitHeavyTail_0.2.0.zip, r-release: fitHeavyTail_0.2.0.zip, r-oldrel: fitHeavyTail_0.2.0.zip
macOS binaries: r-release (arm64): fitHeavyTail_0.2.0.tgz, r-oldrel (arm64): fitHeavyTail_0.2.0.tgz, r-release (x86_64): fitHeavyTail_0.2.0.tgz, r-oldrel (x86_64): fitHeavyTail_0.2.0.tgz
Old sources: fitHeavyTail archive

Reverse dependencies:

Reverse imports: highOrderPortfolios

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