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BSL
Bayesian Synthetic Likelihood
View on CRAN: Click
here
Download and install BSL package within the R console
Install from CRAN:
install.packages("BSL")
Install from Github:
library("remotes")
install_github("cran/BSL") Install by package version:
library("remotes")
install_version("BSL", "3.2.5") Attach the package and use:
library("BSL")
Maintained by
Leah F. South
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-03-23
Latest Update: 2022-11-03
Description:
Bayesian synthetic likelihood (BSL, Price et al. (2018) )
is an alternative to standard, non-parametric approximate Bayesian
computation (ABC). BSL assumes a multivariate normal distribution
for the summary statistic likelihood and it is suitable when the
distribution of the model summary statistics is sufficiently regular.
This package provides a Metropolis Hastings Markov chain Monte Carlo
implementation of four methods (BSL, uBSL, semiBSL and BSLmisspec) and two
shrinkage estimators (graphical lasso and Warton's estimator).
uBSL (Price et al. (2018) ) uses
an unbiased estimator to the normal density. A semi-parametric version
of BSL (semiBSL, An et al. (2018) ) is more robust
to non-normal summary statistics. BSLmisspec (Frazier et al. 2019
) estimates the Gaussian synthetic likelihood whilst
acknowledging that there may be incompatibility between the model and the
observed summary statistic. Shrinkage estimation can help to decrease the
number of model simulations when the dimension of the summary statistic is
high (e.g., BSLasso, An et al. (2019) ).
Extensions to this package are planned. For a journal article describing how
to use this package, see An et al. (2022) .
How to cite:
Leah F. South (2018). BSL: Bayesian Synthetic Likelihood. R package version 3.2.5, https://cran.r-project.org/web/packages/BSL. Accessed 08 Mar. 2026.
Previous versions and publish date:
Other packages that cited BSL R package
View BSL citation profile
Other R packages that BSL depends,
imports, suggests or enhances
Complete documentation for BSL
Functions, R codes and Examples using
the BSL R package
Some associated functions: BSL-class . BSL-package . MODEL-class . PENALTY-class . bsl . cell . combinePlotsBSL . cor2cov . estimateLoglike . estimateWhiteningMatrix . gaussianRankCorr . gaussianSynLike . gaussianSynLikeGhuryeOlkin . getGamma . getLoglike . getPenalty . getTheta . ma2 . mgnk . myMiniProgressBar . obsMat2deltax . rstable . selectPenalty . semiparaKernelEstimate . sim_toad . simulate_cell . simulation . sliceGammaMean . sliceGammaVariance . summStat . synLikeMisspec . toad .
Some associated R codes: BSL-package.R . RcppExports.R . bsl.R . cell.R . combinePlotsBSL.R . covWarton.R . estimateLoglike.R . estimateWhiteningMatrix.R . gaussianRankCorr.R . gaussianSynLike.R . gaussianSynLikeGhuryeOlkin.R . imports.R . kernelCDF.R . logitTransform.R . ma2.R . mgnk.R . myMiniProgressBar.R . s4-BSL.R . s4-MODEL.R . s4-PENALTY.R . selectPenalty.R . semiparaKernelEstimate.R . sliceGammaMean.R . sliceGammaVariance.R . synLikeMisspec.R . toad.R . Full BSL package functions and examples
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