Penalized Likelihood Factor Analysis via Nonconvex Penalty

Kei Hirose, Michio Yamamoto, Haruhisa Nagata

Computes the penalized maximum likelihood estimates of factor loadings and unique variances for various tuning parameters. The pathwise coordinate descent along with EM algorithm is used.  This package also includes a new graphical tool which outputs path diagram, goodness-of-fit indices and model selection criteria for each regularization parameter. The user can change the regularization parameter by manipulating scrollbars, which is helpful to find a suitable value of regularization parameter.

c(person(given = "Kei",
family = "Hirose",
role = c("aut", "cre"),
email = "mail@keihirose.com",
comment = c(ORCID = "0000-0001-9827-0356")),
person(given = "Michio",
family = "Yamamoto",
role = "aut",
email = "yamamoto.michio.hus@osaka-u.ac.jp"),
person(given = "Haruhisa",
family = "Nagata",
role = "aut"))
Kei Hirose [aut, cre] (<https://orcid.org/0000-0001-9827-0356>),
Michio Yamamoto [aut],
Haruhisa Nagata [aut]

person("Adam", "Rich", email = "adamleerich@gmail.com", role = c("aut", "cre"))
Provides the function fancycut() which is like cut() except
you can mix left open and right open intervals with point values,
intervals that are closed on both ends and intervals that are open on both ends.

c(
person("Adam", "Rich", email = "adamleerich@gmail.com", role = c("aut", "cre")),
person("Richie", "Cotton", email = "richierocks@gmail.com", role = "ctb")
)
Adam Rich [aut, cre],
Richie Cotton [ctb]

Building Kriging models from FANOVA graphs
Jana Fruth, Thomas Muehlenstaedt, Olivier Roustant
sensitivity, igraph, DiceKriging (>= 1.2)

Estimation and plotting of a function's FANOVA graph to
identify the interaction structure and fitting, prediction and
simulation of a kriging model modified by the identified
structure.
sensitivity, igraph0, DiceKriging (>= 1.2)

sensitivity, igraph0, DiceKriging (>= 1.3)

Jana Fruth, Thomas Muehlenstaedt, Olivier Roustant, Malte Jastrow
Estimation and plotting of a function's FANOVA graph to identify the interaction structure and fitting, prediction and simulation of a kriging model modified by the identified structure.
sensitivity, igraph0, DiceKriging (>= 1.4)