Mixtures of Contaminated Gaussian Factor Analyzers
c(person("Martin", "Blostein", role = c("aut", "cre"), email="martin.blostein@gmail.com"),
person("Antonio", "Punzo", role = "ctb"),
person(c("Paul", "D."), "McNicholas", role = c("ctb","ths")))
Performs clustering and classification using the Mixtures of Contaminated Gaussian Factor Analyzers model. Allows for automatic detection of outliers and noise.
Martin Blostein [aut, cre],
Antonio Punzo [ctb],
Paul D. McNicholas [ctb, ths]

c(person("Martin", "Blostein", role = c("aut", "cre"), email="martin.blostein@gmail.com"),
person("Antonio", "Punzo", role = "aut"),
person(c("Paul", "D."), "McNicholas", role = c("aut","ths")))
Clustering and classification using the Mixtures of Contaminated Gaussian Factor Analyzers model. Allows for automatic detection of outliers and noise. Punzo, A, Blostein, M, McNicholas, PD (2017) <arXiv:1408.2128v2>.
Martin Blostein [aut, cre],
Antonio Punzo [aut],
Paul D. McNicholas [aut, ths]

Warnes and Raftery's MCGibbsit MCMC diagnostic
mcgibbsit provides an implementation of Warnes & Raftery's MCGibbsit
run-length diagnostic for a set of (not-necessarily independent) MCMC
sampers.  It combines the estimate error-bounding approach of Raftery
and Lewis with evaulate between verses within chain approach
of Gelman and Rubin.

Gregory R. Warnes <Gregory.R.Warnes@Pfizer.com>, with
contributions by Robert Burrows
mcgibbsit provides an implementation of Warnes & Raftery's
MCGibbsit run-length diagnostic for a set of (not-necessarily
independent) MCMC sampers.  It combines the estimate
error-bounding approach of Raftery and Lewis with evaulate
between verses within chain approach of Gelman and Rubin.

Gregory R. Warnes <greg@warnes.net>, with contributions by
Robert Burrows

Gregory R. Warnes <greg@warnes.net>, Robert Burrows
'mcgibbsit' provides an implementation of Warnes & Raftery's
MCGibbsit run-length diagnostic for a set of (not-necessarily
independent) MCMC samplers.  It combines the estimate error-bounding
approach of the Raftery and Lewis MCMC run length diagnostic with
the between verses within chain approach of the Gelman and
Rubin MCMC convergence diagnostic.