Package: fitHeavyTail 0.2.0.9000

Daniel P. Palomar

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).

Authors:Daniel P. Palomar [cre, aut], Rui Zhou [aut], Xiwen Wang [aut], Frédéric Pascal [ctb], Esa Ollila [ctb]

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Peer review:

Bug tracker:https://github.com/convexfi/fitheavytail/issues

On CRAN:

cauchycovariance-estimationcovariance-matrixheavy-tailed-distributionsoutliersrobust-estimationstudent-ttyler

6 exports 20 stars 2.23 score 15 dependencies 1 dependents 27 scripts 1.1k downloads

Last updated 1 years agofrom:f0d576e60d. Checks:OK: 7. Indexed: yes.

Exports:fit_Cauchyfit_mvstfit_mvtfit_Tylernu_OPP_estimatornu_POP_estimator

Dependencies:DBIghypICSICSNPlatticeMASSMatrixminqamitoolsmvtnormnumDerivRcppRcppArmadillosurveysurvival