Package: occTest
Title: Characterizing and Filtering Species Occurrence Data
Version: 0.1
Authors@R: c(person(given = "Josep M", family = "Serra-Diaz", email = "pep.agroparistech@gmail.com",
role = c("aut", "cre")),
person(given = "Cory", family = "Merow", role = c("aut","ctb"),
comment = "Cory co-developped the structure for testing blocks"),
person(given = "Jeremy", family = "Borderieux", role = "ctb",
comment="Jeremy developped plotting and filtering functions"),
person(given = "Brian", family = "Maitner", role = "ctb",
comment = "Brian developped and incorporated centroid and GNRS analysis")
)
Description: Perform multiple tests for potential errors in species occurrence data and filter, and filter data according to users specifications.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.2.1
VignetteBuilder: knitr
Imports: raster, data.table, rgeos, rgdal, biogeo, stringr, alphahull,
plyr, sp, sf, methods, stats, utils, outliers,
CoordinateCleaner, tictoc, rgbif, countrycode, rnaturalearth,
svMisc, spocc, tidyverse, rnaturalearthdata, pingr, ggplot2,
DT, Matrix, dplyr, graphics, dataPreparation
Suggests: GNRS, testthat, knitr, rmarkdown, rworldmap, cleangeo,
geosphere, originr, parallelsugar, assertthat
Additional_repositories: https://pepbioalerts.github.io/drat
NeedsCompilation: no
Packaged: 2022-10-10 07:20:41 UTC; pserra
Author: Josep M Serra-Diaz [aut, cre],
Cory Merow [aut, ctb] (Cory co-developped the structure for testing
blocks),
Jeremy Borderieux [ctb] (Jeremy developped plotting and filtering
functions),
Brian Maitner [ctb] (Brian developped and incorporated centroid and
GNRS analysis)
Maintainer: Josep M Serra-Diaz <pep.agroparistech@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2022-10-10 17:00:05 UTC

Title: Probability Functions for Occupancy Distributions
Authors@R: person("Ben", "O'Neill", email = "ben.oneill@hotmail.com",
Description: The classical and extended occupancy distributions occur in cases where balls are randomly allocated
to bins. The PDF, CDF, quantile functions, generation of random variates, and calculating
the first four central moments of the distributions are implemented as described in