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An implementation of four stochastic methods of integrating in R, including: 1. Stochastic Point Method (or Monte Carlo Method); 2. Mean Value Method; 3. Important Sampling Method; 4. Stratified Sampling Method. It can be used to estimate one-dimension or multi-dimension integration by Monte Carlo methods. And the estimated variance (precision) is given. Reference: Caflisch, R. E. (1998) <doi:10.1017/S0962492900002804>.
| Version: | 0.2.0 |
| Depends: | R (≥ 3.0.1), stats (≥ 3.3.2) |
| Suggests: | knitr, rmarkdown, testthat |
| Published: | 2018-09-23 |
| DOI: | 10.32614/CRAN.package.SI |
| Author: | Jinhong Du |
| Maintainer: | Jinhong Du <jayduking at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | SI results [issues need fixing before 2025-01-10] |
| Reference manual: | SI.pdf |
| Vignettes: |
Monte Carlo Integration |
| Package source: | SI_0.2.0.tar.gz |
| Windows binaries: | r-devel: SI_0.2.0.zip, r-release: SI_0.2.0.zip, r-oldrel: SI_0.2.0.zip |
| macOS binaries: | r-release (arm64): SI_0.2.0.tgz, r-oldrel (arm64): SI_0.2.0.tgz, r-release (x86_64): SI_0.2.0.tgz, r-oldrel (x86_64): SI_0.2.0.tgz |
| Old sources: | SI 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.