lavaan (>= 0.6-9), igraph (>= 1.0-0), qgraph, data.tree,
MIIVsem(>= 0.5.4), imputeTS(>= 3.0), nloptr, graphics, stats,
mvtnorm, MASS, aTSA

Supplemental Tools for the 'gimme' R Package
person("Stephanie", "Lane", email = "lane.stephanie.t@gmail.com", role = c("aut", "cre"))
Supplemental tools for the 'gimme' R package. It contains an interactive graphical user interface, allowing for the flexible specification of a variety of both basic and advanced options. It will expand to include a variety of tools for navigating output.
shiny, shinyjs, rintrojs, easycsv, miniUI, shinyWidgets,
rstudioapi, rhandsontable, magrittr

We provide a set of functions to retrieve information about GIMMS NDVI3g
files currently available online; download and re-arrange the bi-monthly
datasets according to creation time; import downloaded files from native
binary (ENVI) format directly into R based on the widely applied 'raster'
package; and calculate monthly value composites (e.g. maximum value
composites, MVC) from the bi-monthly input data.

We provide a set of functions to retrieve information about GIMMS
NDVI3g files currently available online; download and re-arrange the bi-monthly
datasets according to creation time; import downloaded files from native binary
(ENVI) format directly into R based on the widely applied 'raster' package;
calculate monthly value composites (e.g. maximum value composites, MVC) from the
bi-monthly input data; and derive long-term monotonous trends from the
Mann-Kendall trend test, optionally featuring pre-whitening to
account for lag-1 autocorrelation.

person("Florian", "Detsch", email = "admin@environmentalinformatics-marburg.de", role = c("cre", "aut"))
parallel, doParallel, foreach, Kendall, zyp

We provide a set of functions to retrieve information about GIMMS NDVI3g files currently available online; download and re-arrange the bi-monthly datasets according to creation time; import downloaded files from native binary (ENVI) format directly into R based on the widely applied 'raster' package; extract accompanying quality flags and perform quality control; calculate monthly value composites (e.g. maximum value composites, MVC) from the bi-monthly input data; and derive long-term monotonous trends from the Mann-Kendall trend test, optionally featuring pre-whitening to account for lag-1 autocorrelation.