Package: ZVCV
Type: Package
Title: Zero-Variance Control Variates
Version: 2.1.2
Date: 2022-11-02
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., 2018 <arXiv:1811.05073>), control functionals (CF, Oates et al. (2017) <doi:10.1111/rssb.12185>) and semi-exact control functionals (SECF, South et al., 2020 <arXiv:2002.00033>). 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: 7.1.1
NeedsCompilation: yes
Packaged: 2022-11-02 05:22:03 UTC; southl
Author: Leah F. South [aut, cre] (<https://orcid.org/0000-0002-5646-2963>)
Maintainer: Leah F. South <leah.south@hdr.qut.edu.au>
Repository: CRAN
Date/Publication: 2022-11-02 09:30:19 UTC
Built: R 4.4.0; x86_64-apple-darwin20; 2024-04-08 04:51:16 UTC; unix
Archs: ZVCV.so.dSYM
