Boltzmann Entropy of a Landscape Gradient
Calculates the Boltzmann entropy of a landscape gradient.
It uses the analytical method created by Gao, P., Zhang, H. and Li, Z., 2018
(<doi:10.1111/tgis.12315>).
c(person("Jakub", "Nowosad",
email = "nowosad.jakub@gmail.com",
role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-1057-3721")),
person("Space Informatics Lab", role = c("cph"))
)
Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>),
Space Informatics Lab [cph]

testthat, sp, raster, covr, knitr, rmarkdown, ggplot2,
rasterVis

Calculates the Boltzmann entropy of a landscape gradient.
This package uses the analytical method created by Gao, P., Zhang, H.
and Li, Z., 2018 (<doi:10.1111/tgis.12315>). It also extend the original
idea by allowing calculations on data with missing values.

Calculates the Boltzmann entropy of a landscape gradient.
This package uses the analytical method created by Gao, P., Zhang, H.
and Li, Z., 2018 (<doi:10.1111/tgis.12315>) and by Gao, P. and Li, Z., 2019
(<doi:10.1007/s10980-019-00854-3>). It also extend the original ideas by
allowing calculations on data with missing values.

testthat, sp, covr, knitr, rmarkdown, ggplot2, rasterVis

testthat, sf, sp, stars, covr, knitr, rmarkdown, ggplot2,
rasterVis

testthat, sp, raster, rgdal, covr, knitr, rmarkdown, ggplot2,
rasterVis, stars, terra

Contains basic functions to manipulate belief functions and
associated mass assignments
N. Maillet, B. Charnomordic, S. Destercke
S. Destercke <sebastien.destercke@cirad.fr>, B.
Charnomordic <bch@supagro.inra.fr>
This package contains basic functions to manipulate belief
functions and associated mass assignments (currently on finite
spaces only). It is aimed at providing a basic skeleton for
belief function applications using R.

Count Regression Models Based on the Bell Distribution
c(person(given = "Fabio", family = "Demarqui", email = "fndemarqui@est.ufmg.br", role = c("aut", "cre"),  comment = c(ORCID = "0000-0001-9236-1986")),
person(given = "Marcos", family = "Prates", role = "ctb",  comment = c(ORCID = "0000-0001-8077-4898")),
person(given = "Fredy", family = "Caceres", role = "ctb",  comment = c(ORCID = "0000-0001-8077-4898")))
Bell regression models for count data with overdispersion. The implemented models account for ordinary and zero-inflated regression models under both frequentist and Bayesian approaches. Theoretical details regarding the models implemented in the package can be found in Castellares et al. (2018) <doi:10.1016/j.apm.2017.12.014> and Lemonte et al. (2020) <doi:10.1080/02664763.2019.1636940>.
extraDistr, Formula, magic, MASS, methods, numbers, Rcpp (>=
0.12.0), Rdpack, rstan (>= 2.18.1), rstantools (>= 2.0.0)