R (>= 3.0), network (>= 1.13),networkDynamic (>=
0.9),animation (>= 2.4),sna

tergm (>= 3.6), tsna, testthat, knitr, htmlwidgets,
scatterplot3d

tergm (>= 3.6), ergm, tsna, testthat, knitr, htmlwidgets,
scatterplot3d

c( person("Skye", "Bender-deMoll", role=c("cre","aut"),
email="skyebend@uw.edu"), person("Martina", "Morris",
role=c("ctb"), email="morrism@u.washington.edu"))
R (>= 2.15), network (>= 1.7.2),networkDynamic (>=
0.4.1),animation,sna,statnet.common
Renders dynamic network data from networkDynamic objects
as animated movies or other representations of relational
structure and node attributes that change over time.
Skye Bender-deMoll [cre, aut], Martina Morris [ctb]

Renders dynamic network data from networkDynamic objects as animated movies or other representations of relational structure and node attributes that change over time.

R (>= 3.0), network (>= 1.8),networkDynamic (>=
0.5),animation,sna,statnet.common

R (>= 3.0), network (>= 1.9),networkDynamic (>=
0.6),animation,sna

R (>= 3.0), network (>= 1.12),networkDynamic (>=
0.6),animation (>= 2.3),sna
Renders dynamic network data from "networkDynamic" objects as animated movies or other representations of relational structure and node attributes that change over time.

tergm (>= 3.1), tsna,testthat, knitr, htmlwidgets,
scatterplot3d

NDVI Time series extraction and analysis
R (>= 2.10), gstat, rgdal, bfast, RTisean, RColorBrewer,
lattice
The routines extract automatically, for area of interest,
Normalized Difference Vegetation Index (NDVI) time series from
different optical satellite instruments (AVHRR, Spot
Vegetation) and to provide tools to display and analyze the
time series.Functions have been developed to study landscapes
and more especially to detect changes in land use land cover.
Phenological metrics can be computed for every season as well
as vegetation anomaly maps.

c(person("Yves", "Croissant", role = c("aut", "cre"), email = "yves.croissant@univ-reunion.fr", comment = c(ORCID = "0000-0002-4857-7736")))
knitr, pscl, MASS, AER, lmtest, mlogit, modelsummary,
bookdown, ggplot2
The Vuong test <doi:10.2307/1912557> is a very popular test for non-nested models.
Shi <doi:10.3982/QE382> proposed a non-degenerate version of the Vuong test using local asymptotic theory.