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mined: Minimum Energy Designs

This is a method (MinED) for mining probability distributions using deterministic sampling which is proposed by Joseph, Wang, Gu, Lv, and Tuo (2019) <doi:10.1080/00401706.2018.1552203>. The MinED samples can be used for approximating the target distribution. They can be generated from a density function that is known only up to a proportionality constant and thus, it might find applications in Bayesian computation. Moreover, the MinED samples are generated with much fewer evaluations of the density function compared to random sampling-based methods such as MCMC and therefore, this method will be especially useful when the unnormalized posterior is expensive or time consuming to evaluate. This research is supported by a U.S. National Science Foundation grant DMS-1712642.

Version: 1.0-3
Imports: Rcpp (≥ 0.12.17)
LinkingTo: Rcpp, RcppEigen
Published: 2022-06-26
DOI: 10.32614/CRAN.package.mined
Author: Dianpeng Wang and V. Roshan Joseph
Maintainer: Dianpeng Wang <wdp at bit.edu.cn>
License: LGPL-2.1
NeedsCompilation: yes
CRAN checks: mined results

Documentation:

Reference manual: mined.pdf

Downloads:

Package source: mined_1.0-3.tar.gz
Windows binaries: r-devel: mined_1.0-3.zip, r-release: mined_1.0-3.zip, r-oldrel: mined_1.0-3.zip
macOS binaries: r-release (arm64): mined_1.0-3.tgz, r-oldrel (arm64): mined_1.0-3.tgz, r-release (x86_64): mined_1.0-3.tgz, r-oldrel (x86_64): mined_1.0-3.tgz
Old sources: mined archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mined 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.
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