The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
Empirical likelihood-based approximate Bayesian Computation. Approximates the required posterior using empirical likelihood and estimated differential entropy. This is achieved without requiring any specification of the likelihood or estimating equations that connects the observations with the underlying parameters. The procedure is known to be posterior consistent. More details can be found in Chaudhuri, Ghosh, and Kim (2024) <doi:10.1002/SAM.11711>.
| Version: | 1.0 |
| Imports: | MASS, emplik, methods, FNN, corpcor |
| Published: | 2025-11-21 |
| DOI: | 10.32614/CRAN.package.abcel |
| Author: | Nicholas Chua [aut], Riddhimoy Ghosh [aut], Sanjay Chaudhuri [aut, cre] |
| Maintainer: | Sanjay Chaudhuri <schaudhuri2 at unl.edu> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| CRAN checks: | abcel results |
| Reference manual: | abcel.html , abcel.pdf |
| Package source: | abcel_1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: abcel_1.0.zip |
| macOS binaries: | r-release (arm64): abcel_1.0.tgz, r-oldrel (arm64): abcel_1.0.tgz, r-release (x86_64): abcel_1.0.tgz, r-oldrel (x86_64): abcel_1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=abcel to link to this page.
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.