Package: ZVCV
Type: Package
Title: Zero-Variance Control Variates
Version: 2.1.3
Date: 2025-10-18
Authors@R: c(person("Leah F.","South",role=c("aut","cre"),email="leah.south@hdr.qut.edu.au",comment = c(ORCID = "0000-0002-5646-2963")))
Description: 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. 
BugReports: https://github.com/LeahPrice/ZVCV/issues
License: GPL (>= 2)
LazyLoad: yes
Imports: Rcpp (>= 0.11.0), glmnet, abind, mvtnorm, stats, Rlinsolve,
        magrittr, dplyr
Suggests: partitions, ggplot2, ggthemes
LinkingTo: Rcpp, RcppArmadillo, BH
LazyData: true
Encoding: UTF-8
RoxygenNote: 7.3.1
NeedsCompilation: yes
Packaged: 2025-10-21 01:07:36 UTC; southl
Author: Leah F. South [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-5646-2963>)
Maintainer: Leah F. South <leah.south@hdr.qut.edu.au>
Repository: CRAN
Date/Publication: 2025-10-21 02:20:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-25 21:08:22 UTC; unix
Archs: ZVCV.so.dSYM
