Package: ZVCV 2.1.2
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., 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.
Authors:
ZVCV_2.1.2.tar.gz
ZVCV_2.1.2.tar.gz(r-4.5-noble)ZVCV_2.1.2.tar.gz(r-4.4-noble)
ZVCV_2.1.2.tgz(r-4.4-emscripten)ZVCV_2.1.2.tgz(r-4.3-emscripten)
ZVCV.pdf |ZVCV.html✨
ZVCV/json (API)
NEWS
# Install 'ZVCV' in R: |
install.packages('ZVCV', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/leahprice/zvcv/issues
- VDP - Example of estimation using SMC
Last updated 2 years agofrom:58476ca4db. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 02 2024 |
R-4.5-linux-x86_64 | OK | Dec 02 2024 |
Exports:aSECFaSECF_crossvalCFCF_crossvalevidence_CTIevidence_CTI_CFevidence_SMCevidence_SMC_CFExpand_TemperaturesgetXK0_fnlogsumexpmedianTunenearPDPhi_fnSECFSECF_crossvalsquareNormzvcv
Dependencies:abindBHclicodetoolsdplyrfansiforeachgenericsglmnetglueiteratorslatticelifecyclemagrittrMatrixmvtnormpillarpkgconfigR6rbibutilsRcppRcppArmadilloRcppEigenRdpackrlangRlinsolveshapesurvivaltibbletidyselectutf8vctrswithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Approximate semi-exact control functionals (aSECF) | aSECF |
Approximate semi-exact control functionals (aSECF) with cross-validation | aSECF_crossval |
Control functionals (CF) | CF |
Control functionals (CF) with cross-validation | CF_crossval |
Evidence estimation with ZV-CV | evidence evidence_CTI evidence_CTI_CF evidence_SMC evidence_SMC_CF |
Adjusting the temperature schedule | Expand_Temperatures |
ZV-CV design matrix | getX |
Kernel matrix calculation | K0_fn |
Stable log sum of exponential calculations | logsumexp |
Median heuristic | medianTune |
Nearest symmetric positive definite matrix | nearPD |
Phi matrix calculation | Phi_fn |
Semi-exact control functionals (SECF) | SECF |
Semi-exact control functionals (SECF) with cross-validation | SECF_crossval |
Squared norm matrix calculation | squareNorm |
Example of estimation using SMC | VDP |
ZV-CV for general expectations | zvcv |
Zero-Variance Control Variates | ZVCV-package ZVCV |