ZVCV: Zero-Variance Control Variates
Stein control variates can be used to improve Monte Carlo estimates of expectations when the derivatives of the log target are available. This package implements a variety of such methods, including zero-variance control variates (ZV-CV, Mira et al. (2013) <doi:10.1007/s11222-012-9344-6>), regularised ZV-CV (South et al., 2023 <doi:10.1214/22-BA1328>), control functionals (CF, Oates et al. (2017) <doi:10.1111/rssb.12185>) and semi-exact control functionals (SECF, South et al., 2022 <doi:10.1093/biomet/asab036>). ZV-CV is a parametric approach that is exact for (low order) polynomial integrands with Gaussian targets. CF is a non-parametric alternative that offers better than the standard Monte Carlo convergence rates. SECF has both a parametric and a non-parametric component and it offers the advantages of both for an additional computational cost. Functions for applying ZV-CV and CF to two estimators for the normalising constant of the posterior distribution in Bayesian statistics are also supplied in this package. The basic requirements for using the package are a set of samples, derivatives and function evaluations.
| Version: | 2.1.3 |
| Imports: | Rcpp (≥ 0.11.0),glmnet,abind,mvtnorm, stats,Rlinsolve,magrittr,dplyr |
| LinkingTo: | Rcpp,RcppArmadillo,BH |
| Suggests: | partitions,ggplot2,ggthemes |
| Published: | 2025-10-21 |
| DOI: | 10.32614/CRAN.package.ZVCV |
| Author: | Leah F. South [aut, cre] |
| Maintainer: | Leah F. South <leah.south at hdr.qut.edu.au> |
| BugReports: | https://github.com/LeahPrice/ZVCV/issues |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | ZVCV results |
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