Robust estimation methods for the mean vector and covariance matrix from data (possibly containing NAs) under multivariate heavy-tailed distributions such as angular Gaussian (via Tyler's method), Cauchy, and Student's t. Additionally, a factor model structure can be specified for the covariance matrix. The package is based on the papers: Sun, Babu, and Palomar (2014), Sun, Babu, and Palomar (2015), Liu and Rubin (1995), and Zhou, Liu, Kumar, and Palomar (2019).
Version: | 0.1.2 |
Imports: | ICSNP, mvtnorm, stats |
Suggests: | knitr, ggplot2, prettydoc, reshape2, rmarkdown, R.rsp, testthat |
Published: | 2020-01-07 |
Author: | Daniel P. Palomar [cre, aut], Rui Zhou [aut] |
Maintainer: | Daniel P. Palomar <daniel.p.palomar at gmail.com> |
BugReports: | https://github.com/dppalomar/fitHeavyTail/issues |
License: | GPL-3 |
URL: | https://github.com/dppalomar/fitHeavyTail |
NeedsCompilation: | no |
Citation: | fitHeavyTail citation info |
Materials: | README NEWS |
CRAN checks: | fitHeavyTail results |
Reference manual: | fitHeavyTail.pdf |
Vignettes: |
Mean Vector and Covariance Matrix Estimation under Heavy Tails |
Package source: | fitHeavyTail_0.1.2.tar.gz |
Windows binaries: | r-devel: fitHeavyTail_0.1.2.zip, r-release: fitHeavyTail_0.1.2.zip, r-oldrel: fitHeavyTail_0.1.2.zip |
macOS binaries: | r-release: fitHeavyTail_0.1.2.tgz, r-oldrel: fitHeavyTail_0.1.2.tgz |
Old sources: | fitHeavyTail archive |
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