Package: abcel 1.0

Sanjay Chaudhuri

abcel: Empirical Likelihood-Based Approximate Bayesian Computation

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>.

Authors:Nicholas Chua [aut], Riddhimoy Ghosh [aut], Sanjay Chaudhuri [aut, cre]

abcel_1.0.tar.gz
abcel_1.0.zip(r-4.7-any)abcel_1.0.zip(r-4.6-any)
abcel_1.0.tar.gz(r-4.7-any)abcel_1.0.tar.gz(r-4.6-any)
abcel_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
abcel/json (API)

# Install 'abcel' in R:
install.packages('abcel', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 271 downloads 2 exports 10 dependencies

Last updated from:b9f60f8f89. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK148
source / vignettesOK162
linux-release-x86_64OK107
windows-devel-x86_64OK47
windows-release-x86_64OK68
wasm-releaseOK107

Exports:abcelentEst

Dependencies:corpcoremplikFNNlatticeMASSMatrixMatrixModelsquantregSparseMsurvival