Exact Tests for Hardy-Weinberg Proportions
Tests whether a set of genotype counts fits the HW expectations.
Exact tests performed by an efficient algorithm. Included test statistics
are likelihood ratio, probability, U-score and Pearsons X2.
knitr, knitcitations, adegenet, genetics, parallel

knitr, RefManageR, adegenet, genetics, parallel

Tests whether a set of genotype counts fits the HW expectations.
Exact tests performed by an efficient algorithm. Included test statistics
are likelihood ratio, probability, U-score and Pearson's X2.
ggplot2, rmarkdown, knitr, RefManageR, adegenet, genetics,
parallel

Tools for Processing and Analysing Files from the Hydrological
Catchment Model HYPE
Work with model files (setup, input, output) from
the hydrological catchment model HYPE: Streamlined file import and export, standard
evaluation plot routines, diverse post-processing and aggregation routines
for hydrological model analysis.
c(person("Rene", "Capell", role = c("aut", "cre"), email ="rene.capell@smhi.se"),
person("Conrad", "Brendel", role = "aut", email ="conrad.brendel@smhi.se"),
person("Jafet", "Andersson", role = "ctb"),
person("David", "Gustafsson", role = "ctb"),
person("Jude", list("Musuuza", "Lubega"), role = "ctb"))
clipr, data.table (>= 1.9.8), dplyr, grDevices, graphics,
hydroGOF, ncdf4, parallel, pbapply, rlang, sf, stats, stringr,
tidyr, tidyselect, utils
rmarkdown, knitr, htmlwidgets, leaflet, leaflet.extras,
mapview, randomcoloR
Rene Capell [aut, cre],
Conrad Brendel [aut],
Jafet Andersson [ctb],
David Gustafsson [ctb],
Jude Musuuza [ctb],
Jude Lubega [ctb]

clipr, data.table (>= 1.9.8), dplyr, ggplot2, ggpubr,
grDevices, graphics, hydroGOF, ncdf4, parallel, patchwork,
pbapply, purrr, rlang, sf, stats, stringr, tidyr, tidyselect,
utils
rmarkdown, knitr, htmlwidgets, leaflet, leaflet.extras,
mapview, randomcoloR, webshot

Hybrid Methods for Addressing Uncertainty in RISK Assessments
Jeremy Rohmer, Jean-Charles Manceau, Dominique Guyonnet, Faiza Boulahya
Methods for addressing uncertainty in risk assessments using hybrid representations of uncertainty (probability distributions, fuzzy numbers, intervals, probability distributions with imprecise parameters). The uncertainty propagation procedure combines random sampling using Monte Carlo method with fuzzy interval analysis of Baudrit et al. (2007) <doi:10.1109/TFUZZ.2006.876720>. The sensitivity analysis is based on the pinching method of Ferson and Tucker (2006) <doi:10.1016/j.ress.2005.11.052>.
datasets,utils,grDevices,graphics,stats,sets, pbapply, reliaR,
kerdiest, triangle, rgenoud