scatterplot3d, shiny, grDevices, graphics, stats, ggplot2,
ggwordcloud, metR, interp
testthat, rmarkdown, knitr, hexbin, shinycssloaders, shinyBS,
shinyjs, shinyjqui

c(person("Nathalie", "Vialaneix", role = c("aut", "cre"), email="nathalie.vialaneix@inrae.fr"),
person("Elise", "Maigne", role = "aut", email="elise.maigne@inrae.fr"),
person("Jerome", "Mariette", role= "aut", email="jerome.mariette@inrae.fr"),
person("Madalina", "Olteanu", role = "aut", email="olteanu@ceremade.dauphine.fr"),
person("Fabrice", "Rossi", role = "aut", email="fabrice.rossi@apiacoa.org"),
person("Laura", "Bendhaiba", role = "ctb", email="laurabendhaiba@gmail.com"),
person("Julien", "Boelaert", role= "ctb", email="julien.boelaert@gmail.com"))
The stochastic (also called on-line) version of the Self-Organising
Map (SOM) algorithm is provided. Different versions of the
algorithm are implemented, for numeric and relational data and for
contingency tables as described, respectively, in Kohonen (2001)
<isbn:3-540-67921-9>, Olteanu & Villa-Vialaneix (2005)
<doi:10.1016/j.neucom.2013.11.047> and Cottrell et al (2004)
<doi:10.1016/j.neunet.2004.07.010>. The package also contains many
plotting features (to help the user interpret the results), can
handle (and impute) missing values and is delivered with a
graphical user interface based on 'shiny'.

Generalised Additive P-Spline Regression Models Estimation
c(
person(given = "Maria Xose", family = "Rodriguez-Alvarez",
email = "mxrodriguez@bcamath.org", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1329-9238")),
person(given = "Manuel", family = "Oviedo de la Fuente", email = "manuel.ovideo@usc.es", role = c("aut")),
person(given = "Maria", family = "Durban", email = "mdurban@est-econ.uc3m.es", role = c("ctb")),
person(given = "Paul H.C.", family = "Eilers", email = "p.eilers@erasmusmc.nl", role = c("ctb")),
person(given = "Dae-Jin", family = "Lee", email = "dlee@bcamath.org", role = c("ctb")),
person(given = "Mikis", family = "Stasinopoulos", email = "d.stasinopoulos@londonmet.ac.uk", role = c("ctb")))
Generalised additive P-spline regression models estimation using the separation of overlapping precision matrices (SOP) method. Estimation is based on the equivalence between P-splines and linear mixed models, and variance/smoothing parameters are estimated based on restricted maximum likelihood (REML). The package enables users to estimate P-spline models with overlapping penalties. Based on the work described in Rodriguez-Alvarez et al. (2015) <doi:10.1007/s11222-014-9464-2>; Rodriguez-Alvarez et al. (2019) <doi:10.1007/s11222-018-9818-2>, and Eilers and Marx (1996) <doi:10.1214/ss/1038425655>.
Maria Xose Rodriguez-Alvarez [aut, cre]
(<https://orcid.org/0000-0002-1329-9238>),
Manuel Oviedo de la Fuente [aut],
Maria Durban [ctb],
Paul H.C. Eilers [ctb],
Dae-Jin Lee [ctb],
Mikis Stasinopoulos [ctb]