Package: fitHeavyTail
Title: Mean and Covariance Matrix Estimation under Heavy Tails
Version: 0.1.2
Date: 2020-1-7
Description: 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).
Authors@R: c(
  person(c("Daniel", "P."), "Palomar", role = c("cre", "aut"), email = "daniel.p.palomar@gmail.com"),
  person("Rui", "Zhou", role =  "aut", email = "rzhouae@connect.ust.hk")
  )
Maintainer: Daniel P. Palomar <daniel.p.palomar@gmail.com>
URL: https://github.com/dppalomar/fitHeavyTail
BugReports: https://github.com/dppalomar/fitHeavyTail/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Depends:
Imports: ICSNP, mvtnorm, stats
Suggests: knitr, ggplot2, prettydoc, reshape2, rmarkdown, R.rsp,
        testthat
VignetteBuilder: knitr, rmarkdown, R.rsp
NeedsCompilation: no
Packaged: 2020-01-07 01:43:11 UTC; palomar
Author: Daniel P. Palomar [cre, aut],
  Rui Zhou [aut]
Repository: CRAN
Date/Publication: 2020-01-07 10:20:02 UTC
Built: R 4.0.2; ; 2020-07-16 21:16:59 UTC; unix
