Exact Goodness-of-Fit Test for Multinomial Data with Fixed
Probabilities
Tests whether a set of counts fit a given expected ratio. For
example, a genetic cross might be expected to produce four types in the
relative frequencies of 9:3:3:1. To see whether a set of observed counts
fits this expectation, one can examine all possible outcomes with xmulti() or a
random sample of them with xmonte() and find the probability of an observation
deviating from the expectation by at least as much as the observed. As a
measure of deviation from the expected, one can use the log-likelihood
ratio, the multinomial probability, or the classic chi-square statistic. A
histogram of the test statistic can also be plotted and compared with the
asymptotic curve.

c(
person("Luiz", "Moro Rosso", email = "lhmrosso@ksu.edu", role = "cre"),
person("Andre", "Borja Reis", email = "andrefbr@ksu.edu", role = "aut"),
person("Adrian", "Correndo", email = "correndo@ksu.edu", role = "aut"),
person("Ignacio", "Ciampitti", email = "ciampitti@ksu.edu", role = "aut"))
The POLARIS database <http://hydrology.cee.duke.edu/POLARIS/>
is a 30-meter probabilistic soil series map of the contiguous United
States (US). It represents an optimization of the Soil Survey
Geographic database. This R package facilitates the access
to large amounts of soil data within the US, currently
stored online as raster images (TIFF).
covr, knitr, mapproj, maps, methods, rgdal, rmarkdown,
testthat (>= 3.0.0)
dplyr, ggplot2, magrittr, purrr, raster, sf, tidyr, utils
Luiz Moro Rosso [cre],
Andre Borja Reis [aut],
Adrian Correndo [aut],
Ignacio Ciampitti [aut]

covr, knitr, mapproj, maps, methods, rgdal, rlang, rmarkdown,
testthat (>= 3.0.0)
curl, dplyr, ggplot2, httr, magrittr, purrr, raster, sf,
tidyr, utils

Support for interfaces from R to other languages,
built around a class for evaluators and a combination of functions, classes and
methods for communication. Will be used through a specific language interface
package. Described in the book "Extending R".