Package: mined
Type: Package
Title: Minimum Energy Designs
Version: 1.0-3
Date: 2022-06-19
Author: Dianpeng Wang and V. Roshan Joseph
Maintainer: Dianpeng Wang <wdp@bit.edu.cn>
Description: 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.
License: LGPL-2.1
Imports: Rcpp (>= 0.12.17)
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2022-06-19 06:37:01 UTC; dpwang
Repository: CRAN
Date/Publication: 2022-06-26 21:30:02 UTC
Built: R 4.2.0; aarch64-apple-darwin20; 2022-06-26 22:03:33 UTC; unix
Archs: mined.so.dSYM
