c(person("Julian", "Faraway", role = "aut"),
person("George", "Marsaglia", role = "aut"),
person("John",   "Marsaglia", role = "aut"),
person("Adrian", "Baddeley", role = c("aut", "cre"),
email = "Adrian.Baddeley@curtin.edu.au"))

Extension of 'gof ' package to survival models.
Archived on 2017-05-15 for policy violation.

Extension of 'gof' package to survival models.

Easy and flexible interface for manipulating go game (weiqi, baduk) data.
The package features a reader function for SGF (smart go format) text files,
and a set of plotting functions that draw go board images.
dplyr, ggplot2, graphics, gridExtra, magrittr, scales, stats,
stringr, Rcpp, utils,

Generalized Orthogonal GARCH (GO-GARCH) models
R (>= 2.7.0), methods, stats, graphics, fGarch, fastICA
Implementation of the GO-GARCH model class

R (>= 2.10.0), methods, stats, graphics, fGarch, fastICA

person("Bernhard", "Pfaff", email = "bernhard@pfaffikus.de",
role = c("aut", "cre"))

Generalized Orthogonal GARCH (GO-GARCH) Models
Provision of classes and methods for estimating generalized
orthogonal GARCH models. This is an alternative approach to CC-GARCH models
in the context of multivariate volatility modeling.
person("Bernhard", "Pfaff",
email = "bernhard@pfaffikus.de", role = c("aut", "cre"))

Statistical Network Models for Dynamic Network Data
c(person("James", "Hollway", role = c("cre", "aut", "dtc"),
email = "james.hollway@graduateinstitute.ch",
comment = c("IHEID", ORCID = "0000-0002-8361-9647")),
person("Christoph", "Stadtfeld", role = c("aut", "dtc"),
email = "c.stadtfeld@ethz.ch"),
person("Marion", "Hoffman", role = "ctb"),
person("Alvaro", "Uzaheta", role = "ctb",
comment = c(ORCID = "0000-0003-4367-3670")),
person("Mirko", "Reul", role = "ctb"),
person("Timon", "Elmer", role = "ctb"),
person("Kieran", "Mepham", role = "ctb"),
person("Per", "Block", role = "ctb"),
person("Xiaolei", "Zhang", role = "ctb"),
person("Weigutian", "Ou", role = "ctb"),
person("Emily", "Garvin", role = "ctb"),
person("Siwei", "Zhang", role = "ctb"))
Tools for fitting statistical network models to dynamic network data.
Can be used for fitting both dynamic network actor models ('DyNAMs') and
relational event models ('REMs').
Stadtfeld, Hollway, and Block (2017a) <doi:10.1177/0081175017709295>,
Stadtfeld, Hollway, and Block (2017b) <doi:10.1177/0081175017733457>,
Stadtfeld and Block (2017) <doi:10.15195/v4.a14>,
Hoffman et al. (2020) <doi:10.1017/nws.2020.3>.
Rcpp (>= 1.0.1), changepoint, methods, utils, stats, generics,
ggplot2, tibble
testthat, knitr, devtools, covr, rmarkdown, pixiedust,
igraph, ggraph, migraph, broom, lmtest
James Hollway [cre, aut, dtc] (IHEID,
<https://orcid.org/0000-0002-8361-9647>),
Christoph Stadtfeld [aut, dtc],
Marion Hoffman [ctb],
Alvaro Uzaheta [ctb] (<https://orcid.org/0000-0003-4367-3670>),
Mirko Reul [ctb],
Timon Elmer [ctb],
Kieran Mepham [ctb],
Per Block [ctb],
Xiaolei Zhang [ctb],
Weigutian Ou [ctb],
Emily Garvin [ctb],
Siwei Zhang [ctb]