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 |
| 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 |
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