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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).
Getting started
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Package details |
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| 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@gmail.com> |
| License | GPL-3 |
| Version | 0.2.0 |
| 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 |
| Package repository | View on CRAN |
| Installation |
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