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nimbleHMC  

Hamiltonian Monte Carlo and Other Gradient-Based MCMC Sampling Algorithms for 'nimble'
View on CRAN: Click here


Download and install nimbleHMC package within the R console
Install from CRAN:
install.packages("nimbleHMC")

Install from Github:
library("remotes")
install_github("cran/nimbleHMC")

Install by package version:
library("remotes")
install_version("nimbleHMC", "0.2.1")



Attach the package and use:
library("nimbleHMC")
Maintained by
Daniel Turek
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-05-31
Latest Update: 2024-02-08
Description:
Provides gradient-based MCMC sampling algorithms for use with the MCMC engine provided by the 'nimble' package. This includes two versions of Hamiltonian Monte Carlo (HMC) No-U-Turn (NUTS) sampling, and (under development) Langevin samplers. The `NUTS_classic` sampler implements the original HMC-NUTS algorithm as described in Hoffman and Gelman (2014) . The `NUTS` sampler is a modern version of HMC-NUTS sampling matching the HMC sampler available in version 2.32.2 of Stan (Stan Development Team, 2023). In addition, convenience functions are provided for generating and modifying MCMC configuration objects which employ HMC sampling.
How to cite:
Daniel Turek (2023). nimbleHMC: Hamiltonian Monte Carlo and Other Gradient-Based MCMC Sampling Algorithms for 'nimble'. R package version 0.2.1, https://cran.r-project.org/web/packages/nimbleHMC
Previous versions and publish date:
0.1.0 (2023-05-31 11:00), 0.1.1 (2023-07-07 13:50), 0.2.0 (2023-09-12 04:20)
Other packages that cited nimbleHMC R package
View nimbleHMC citation profile
Other R packages that nimbleHMC depends, imports, suggests or enhances
Functions, R codes and Examples using the nimbleHMC R package
Some associated functions: addHMC . buildHMC . configureHMC . nimbleHMC . sampler_NUTS . sampler_NUTS_classic . stateNL_NUTS . treebranchNL_NUTS . 
Some associated R codes: HMC_configuration.R . HMC_samplers.R .  Full nimbleHMC package functions and examples
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