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An implementation of the Monte Carlo techniques described in details by Dufour (2006) <doi:10.1016/j.jeconom.2005.06.007> and Dufour and Khalaf (2007) <doi:10.1002/9780470996249.ch24>. 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.
Version: | 0.1.2 |
Imports: | GenSA, pso, GA, NMOF, scales, stats, graphics, utils |
Suggests: | fUnitRoots, microbenchmark, boot, MASS, knitr, rmarkdown |
Published: | 2024-10-02 |
DOI: | 10.32614/CRAN.package.MaxMC |
Author: | Julien Neves [aut], Jean-Marie Dufour [aut, ths], Gabriel Rodriguez-Rondon [cre] |
Maintainer: | Gabriel Rodriguez-Rondon <gabriel.rodriguezrondon at mail.mcgill.ca> |
License: | GPL (≥ 3) |
URL: | https://github.com/julienneves/MaxMC |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | MaxMC results |
Reference manual: | MaxMC.pdf |
Package source: | MaxMC_0.1.2.tar.gz |
Windows binaries: | r-devel: MaxMC_0.1.2.zip, r-release: MaxMC_0.1.2.zip, r-oldrel: MaxMC_0.1.2.zip |
macOS binaries: | r-release (arm64): MaxMC_0.1.2.tgz, r-oldrel (arm64): MaxMC_0.1.2.tgz, r-release (x86_64): MaxMC_0.1.2.tgz, r-oldrel (x86_64): MaxMC_0.1.2.tgz |
Old sources: | MaxMC archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.