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MaxMC  

Maximized Monte Carlo
View on CRAN: Click here


Download and install MaxMC package within the R console
Install from CRAN:
install.packages("MaxMC")

Install from Github:
library("remotes")
install_github("cran/MaxMC")

Install by package version:
library("remotes")
install_version("MaxMC", "0.1.2")



Attach the package and use:
library("MaxMC")
Maintained by
Gabriel Rodriguez-Rondon
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-03-24
Latest Update: 2024-10-02
Description:
An implementation of the Monte Carlo techniques described in details by Dufour (2006) and Dufour and Khalaf (2007) . The two main features available are the Monte Carlo method with tie-breaker, mc(), for discrete statistics, and the Maximized Monte Carlo, mmc(), for statistics with nuisance parameters.
How to cite:
Gabriel Rodriguez-Rondon (2019). MaxMC: Maximized Monte Carlo. R package version 0.1.2, https://cran.r-project.org/web/packages/MaxMC. Accessed 30 Oct. 2026.
Previous versions and publish date:
0.1.1 (2019-03-24 10:06), (2026-07-09 08:10)
Other packages that cited MaxMC R package
View MaxMC citation profile
Other R packages that MaxMC depends, imports, suggests or enhances
Complete documentation for MaxMC
Functions, R codes and Examples using the MaxMC R package
Some associated functions: MaxMC-package . get_control . mc . mmc . monitor_mmc . plot.mmc . print.mc . print.mmc . pvalue . return_mc . return_mmc . simulation_mc . simulation_mmc . 
Some associated R codes: classes.R . controls.R . mc.R . mmc.R . monitor.R . plot.R . print.R . pvalue.R . simulation.R .  Full MaxMC package functions and examples
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