Package: mc2d 0.2.1
Regis Pouillot
mc2d: Tools for Two-Dimensional Monte-Carlo Simulations
A complete framework to build and study Two-Dimensional Monte-Carlo simulations, aka Second-Order Monte-Carlo simulations. Also includes various distributions (pert, triangular, Bernoulli, empirical discrete and continuous).
Authors:
mc2d_0.2.1.tar.gz
mc2d_0.2.1.tar.gz(r-4.5-noble)mc2d_0.2.1.tar.gz(r-4.4-noble)
mc2d_0.2.1.tgz(r-4.4-emscripten)mc2d_0.2.1.tgz(r-4.3-emscripten)
mc2d.pdf |mc2d.html✨
mc2d/json (API)
NEWS
| # Install 'mc2d' in R: |
| install.packages('mc2d', repos = 'https://cloud.r-project.org') |
- ec - An example on Escherichia coli in ground beef
- total - An Example of all Kind of mcnode
- x0 - An Example of all Kind of mcnode
- x0M - An Example of all Kind of mcnode
- xU - An Example of all Kind of mcnode
- xUM - An Example of all Kind of mcnode
- xV - An Example of all Kind of mcnode
- xVM - An Example of all Kind of mcnode
- xVU - An Example of all Kind of mcnode
- xVUM - An Example of all Kind of mcnode
- xVUM2 - An Example of all Kind of mcnode
- xVUM3 - An Example of all Kind of mcnode
Conda:r-mc2d-0.2.1(2025-03-25)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:85db1299be. Checks:3 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Apr 02 2025 |
| R-4.5-linux | OK | Apr 02 2025 |
| R-4.4-linux | OK | Apr 02 2025 |
Exports:addvarconvergcornodedberndbetagendbetasubjddirichletdempiricalCdempiricalDdimmcdimmcnodedlnormbdmqidmultinomialdmultinormaldpertdtriangevalmccutevalmcmodextractvargghistgghist.mcgghist.mcnodeggplotmcggplotmc.mcggplotmc.mcnodeggspaghettiggspaghetti.mcggspaghetti.mcnodeggtornadohist.mchist.mcnodeis.finite.mcnodeis.infinite.mcnodeis.mcis.mcnodeis.na.mcnodeis.nan.mcnodelhsmcmcapplymcdatamcdatanocontrolmcmodelmcmodelcutmcprobtreemcratiomcstocnduncndvarOps.mcnodeoutmpbernpbetagenpbetasubjpempiricalCpempiricalDplnormbplot.mcplot.mccutplot.mcnodeplot.plotmcplot.tornadoplot.tornadouncpmaxpmax.defaultpmax.mcnodepminpmin.defaultpmin.mcnodepmqippertprint.mcprint.mccutprint.mcnodeprint.summary.mcprint.tornadoprint.tornadouncptriangqbernqbetagenqbetasubjqempiricalCqempiricalDqlnormbqmqiqpertqtriangquantile.mcquantile.mcnoderbernrbetagenrbetasubjrdirichletrempiricalCrempiricalDrlnormbrmqirmultinomialrmultinormalrpertrtriangrtruncspaghettispaghetti.mcspaghetti.mcnodesummary.mcsummary.mccutsummary.mcnodetornadotornadounctornadounc.defaulttornadounc.mctornadounc.mccuttypemcnodeunmc
Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompurrrquantregR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr
A Manual for mc2d: Tools for Two-Dimensional Monte-Carlo Simulations
Rendered fromdocmcEnglish.Rnwusingutils::Sweaveon Apr 02 2025.Last update: 2023-07-17
Started: 2011-11-14
Case study: L. monocytogenes in cold-smoked salmon
Rendered frommc2dLmEnglish.rnwusingutils::Sweaveon Apr 02 2025.Last update: 2023-07-17
Started: 2011-11-14
Citation
To cite mc2d in publications use:
R. Pouillot, M.-L. Delignette-Muller (2010), Evaluating variability and uncertainty in microbial quantitative risk assessment using two R packages. International Journal of Food Microbiology. 142(3):330-40. DOI 10.1016/j.ijfoodmicro.2010.07.011
Corresponding BibTeX entry:
@Article{,
title = {Evaluating variability and uncertainty in microbial
quantitative risk assessment using two {R} packages},
author = {R. Pouillot and M.-L. Delignette-Muller},
journal = {International Journal of Food Microbiology},
volume = {142},
number = {3},
pages = {330--40},
year = {2010},
doi = {10.1016/j.ijfoodmicro.2010.07.011},
}
Readme and manuals
Tools for Two-Dimensional Monte-Carlo Simulations
The package
mc2d provides a complete framework to build and study Two-Dimensional Monte-Carlo simulations, aka Second-Order Monte-Carlo simulations. It also includes various distributions frequently used in the risk assessment domain (pert, triangular, Bernoulli, empirical discrete and continuous, beta subjective,
Minimum Quantile Information Distribution, ...).
Getting it
The stable version of mc2d can be installed from CRAN using:
install.packages("mc2d")
library("mc2d")
The development version of mc2d can be installed from GitHub (devtools needed):
if (!requireNamespace("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github("rpouillot/mc2d")
library("mc2d")
Check the NEWS here.
Documentation
See the manual and the vignettes distributed with the package.
Issues
Issues can be reported on https://github.com/rpouillot/mc2d/issues.
or directly to the maintainer Régis Pouillot: rpouillot@yahoo.fr
Citations
If you use mc2d, please cite:
R. Pouillot, M.-L. Delignette-Muller (2010), Evaluating variability and uncertainty in microbial quantitative risk assessment using two R packages. International Journal of Food Microbiology. 142(3):330-40