Performs multiple empirical likelihood tests for linear and
generalized linear models. The package offers an easy-to-use interface
and flexibility in specifying hypotheses and calibration methods,
extending the framework to simultaneous inferences. The core
computational routines are implemented using the 'Eigen' C++ library
and 'RcppEigen' interface, with OpenMP for parallel computation.
Details of the testing procedures are given in Kim, MacEachern, and
Peruggia (2021) <arxiv:2112.09206>. This work was supported by the
U.S. National Science Foundation under Grants No. SES-1921523 and
DMS-2015552.

c(person(given = "Hadley",
family = "Wickham",
role = "aut",
email = "hadley@rstudio.com"),
person(given = "Duncan",
family = "Garmonsway",
role = c("aut", "cre"),
email = "nacnudus@gmail.com",
comment = "@nacnudus"),
person(given = "Jim",
family = "Hester",
role = "aut",
email = "jim.hester@rstudio.com",
comment = c(ORCID = "0000-0002-2739-7082")),
person(given = "RStudio",
role = c("cph", "fnd")),
person(given = "https://github.com/mandreyel/",
role = "cph",
comment = "mio library"))
The goal of 'meltr' is to provide a fast and friendly way to
read non-rectangular data, such as ragged forms of csv (comma-separated
values), tsv (tab-separated values), and fwf (fixed-width format) files.
clipr, covr, crayon, curl, readr, testthat (>= 3.0.0), withr
Hadley Wickham [aut],
Duncan Garmonsway [aut, cre] (@nacnudus),
Jim Hester [aut] (<https://orcid.org/0000-0002-2739-7082>),
RStudio [cph, fnd],
https://github.com/mandreyel/ [cph] (mio library)

Matching Event Data by Location, Time and Type
Framework for merging and disambiguating event data based on spatiotemporal co-occurrence and secondary event characteristics. It can account for intrinsic "fuzziness" in the coding of events, varying event taxonomies and different geo-precision codes.
sp, reticulate, graphics, scales, ggmap, ggplot2,
plotGoogleMaps, plyr

utils, ggplot2, plyr, dplyr, reticulate, Rcpp, shiny, shinyjs,
tidyr, leaflet, tibble