jmvcore (>= 1.0.0), evaluate, rappdirs, httr, Rcpp (>=
0.12.16)

jmvcore (>= 1.2.19), evaluate, rappdirs, httr, Rcpp (>=
0.12.16)

jmvcore (>= 1.2.5), evaluate, rappdirs, httr, Rcpp (>=
0.12.16)

jmvcore (>= 2.3.12), evaluate, rappdirs, httr, Rcpp (>=
0.12.16)

'jamovi' is a framework for creating rich interactive statistical
analyses (see <https://www.jamovi.org> for more information). This package
represents the core libraries which jamovi analyses written in R depend
upon.

testthat (>= 1.0.2), RProtoBuf, knitr, ggplot2

A framework for creating rich interactive analyses for the jamovi
platform (see <https://www.jamovi.org> for more information).

R6 (>= 1.0.1), rjson, base64enc, stringi
testthat (>= 1.0.2), RProtoBuf, knitr, ggplot2, RColorBrewer

R6 (>= 1.0.1), rlang (>= 0.3.0.1), jsonlite, base64enc,
stringi

testthat (>= 1.0.2), RProtoBuf, knitr, ggplot2, RColorBrewer,
ragg

testthat (>= 1.0.2), RProtoBuf, knitr, ggplot2, RColorBrewer,
ragg, fastmap

Run Code as an RStudio Job - Free Your Console
person(given = "Jonas Kristoffer",
family = "Lindeløv",
role = c("aut", "cre"),
email = "jonas@lindeloev.dk",
comment = c(ORCID = "0000-0003-4565-0595"))
Call job::job({<code here>}) to run R code as an RStudio job and keep your console free in the meantime. This allows for a productive workflow while testing (multiple) long-running chunks of code. It can also be used to organize results using the RStudio Jobs GUI or to test code in a clean environment. Two RStudio Addins can be used to run selected code as a job.
Jonas Kristoffer Lindeløv [aut, cre]
(<https://orcid.org/0000-0003-4565-0595>)

person("Philip", "Pallmann", role=c("aut", "cre"), email="p.pallmann@lancaster.ac.uk")
Computing and plotting joint confidence regions and intervals. Regions include classical ellipsoids, minimum-volume or minimum-length regions, and an empirical Bayes region. Intervals include the TOST procedure with ordinary or expanded intervals and a fixed-sequence procedure. Such regions and intervals are useful e.g., for the assessment of multi-parameter (bio-)equivalence. Joint confidence regions for the mean and variance of a normal distribution are available as well.