This is a set of functions to retrieve information about GIMMS
NDVI3g files currently available online; download (and re-arrange, in the
case of NDVI3g.v0) the half-monthly data sets; import downloaded files from
ENVI binary (NDVI3g.v0) or NetCDF format (NDVI3g.v1) directly into R based
on the widespread 'raster' package; conduct quality control; and generate
monthly composites (e.g., maximum values) from the half-monthly input data.
As a special gimmick, a method is included to conveniently apply the
Mann-Kendall trend test upon 'Raster*' images, optionally featuring
trend-free pre-whitening to account for lag-1 autocorrelation.

person("Hao", "Zhu", email = "haozhu233@gmail.com", role = c("aut", "cre"))
An interface to the 'API' of 'Giphy', a popular index-based search
engine for 'GIFs' and animated stickers (see <http://giphy.com/faq> and
<https://github.com/Giphy/GiphyAPI> for more information about 'Giphy' and
its 'API') . This package also provides a 'RStudio Addin', which can help
users easily search and download 'GIFs' and insert them to a 'rmarkdown'
presentation.
httr, shiny, miniUI, tibble, rstudioapi, utils, purrr

httr, shiny, miniUI, tibble, rstudioapi, utils, dplyr, purrr

person("Hao", "Zhu", email = "haozhu233@gmail.com",
role = c("aut", "cre"),
comment = c(ORCID = '0000-0002-3386-6076'))

Gaussian Model Invariant by Permutation Symmetry
c(
person("Przemysław", "Chojecki", , "premysl.choj@gmail.com", role = c("aut", "cre")),
person("Paweł", "Morgen", , "seriousmorgen@protonmail.com", role = "aut"),
person("Bartosz", "Kołodziejek", , "b.kolodziejek@mini.pw.edu.pl", role = "aut",
comment = c(ORCID = "0000-0002-5220-9012"))
)
Find the permutation symmetry group such that the covariance
matrix of the given data is invariant under it. Discovering such
a permutation decreases the number of observations needed to fit
a Gaussian model, which is of great use when it is smaller than
the number of variables. Even if that is not the case, the covariance
matrix found with 'gips' approximates the actual covariance with less
statistical error. The methods implemented in this package are
described in Graczyk et al. (2022) <doi:10.1214/22-AOS2174>.
DAAG, dplyr, ggplot2, graphics, HSAUR, knitr, MASS (>=
7.3-39), rmarkdown, spelling, stringi, testthat (>= 3.0.0),
tibble, tidyr, withr
Przemysław Chojecki [aut, cre],
Paweł Morgen [aut],
Bartosz Kołodziejek [aut] (<https://orcid.org/0000-0002-5220-9012>)