distributions such as angular Gaussian (via Tyler's method), Cauchy,
Additionally, a factor model structure can be specified for the covariance
The package is based on the papers: Sun, Babu, and Palomar (2014),
Sun, Babu, and Palomar (2015), Liu and Rubin (1995), and

Description: 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.
person("Rui", "Zhou", role =  "aut", email = "rzhouae@connect.ust.hk"),
person("Xiwen", "Wang", role =  "aut", email = "xwangew@connect.ust.hk")
Imports: ICSNP, mvtnorm, ghyp, numDeriv, stats

Title: Modeling Over Dispersed Binomial Outcome Data Using BMD and ABD
person("Amalan", "Mahendran", email = "amalan0595@gmail.com", role = c("aut","cre")),
person("Pushpakanthie", "Wijekoon", role = c("aut","ctb")))
Description: Contains probability mass functions, cumulative mass functions, negative log likelihood value, parameter estimation and modeling data using Binomial Mixture distributions (BMD) (Manoj et al (2013) <doi:10.5539/ijsp.v2n2p24>) and Alternate Binomial distributions (ABD).

Description: Contains Probability Mass Functions, Cumulative Mass Functions, Negative Log Likelihood value, parameter estimation and modeling data using Binomial Mixture Distributions (BMD) (Manoj et al (2013) <doi:10.5539/ijsp.v2n2p24>) and Alternate Binomial Distributions (ABD) (Paul (1985) <doi:10.1080/03610928508828990>).
person("Amalan","Mahendran", email = "amalan0595@gmail.com", role = c("aut","cre")),
Suggests: testthat, bbmle, devtools, covr

person("Amalan","Mahendran", email = "amalan0595@gmail.com", role = c("aut","cre")
person("Pushpakanthie", "Wijekoon", role = c("aut","ctb")
Author: Amalan Mahendran [aut, cre] (<https://orcid.org/0000-0002-0643-9052>),