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LangevinFlow
View on CRAN: Click
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Download and install LangevinFlow package within the R console
Install from CRAN:
install.packages("LangevinFlow")
Install from Github:
library("remotes")
install_github("cran/LangevinFlow") Install by package version:
library("remotes")
install_version("LangevinFlow", "0.1.0") Attach the package and use:
library("LangevinFlow")
Maintained by
Behrooz Moosavi
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[Scholar Profile | Author Map]
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First Published: 2026-05-29
Latest Update: 2026-05-29
Description:
Provides lightweight, dependency-minimal implementations of Langevin diffusion based Markov chain Monte Carlo samplers, including the Unadjusted Langevin Algorithm (ULA) and the Metropolis-Adjusted Langevin Algorithm (MALA). The core sampling loops are written in C++ via 'Rcpp' and 'RcppArmadillo' for performance, while exposing a simple R-level interface where the user supplies the gradient of the negative log-density (and, for MALA, the negative log-density itself). Intended as a building block for Bayesian inference and stochastic optimization rather than a full probabilistic programming framework. Methods follow Roberts and Tweedie (1996) <doi:10.2307/3318418> and Roberts and Rosenthal (1998) <doi:10.1111/1467-9868.00123>.
How to cite:
Behrooz Moosavi (2026). LangevinFlow: Langevin Diffusion Samplers with a C++ Backend. R package version 0.1.0, https://cran.r-project.org/web/packages/LangevinFlow. Accessed 19 Sep. 2026.
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