Package: fmcmc 0.5-2.9000
George Vega Yon
fmcmc: A friendly MCMC framework
Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC) framework for implementing Metropolis-Hastings algorithm in a modular way allowing users to specify automatic convergence checker, personalized transition kernels, and out-of-the-box multiple MCMC chains using parallel computing. Most of the methods implemented in this package can be found in Brooks et al. (2011, ISBN 9781420079425). Among the methods included, we have: Haario (2001) <doi:10.1007/s11222-011-9269-5> Adaptive Metropolis, Vihola (2012) <doi:10.1007/s11222-011-9269-5> Robust Adaptive Metropolis, and Thawornwattana et al. (2018) <doi:10.1214/17-BA1084> Mirror transition kernels.
Authors:
fmcmc_0.5-2.9000.tar.gz
fmcmc_0.5-2.9000.zip(r-4.5)fmcmc_0.5-2.9000.zip(r-4.4)fmcmc_0.5-2.9000.zip(r-4.3)
fmcmc_0.5-2.9000.tgz(r-4.4-any)fmcmc_0.5-2.9000.tgz(r-4.3-any)
fmcmc_0.5-2.9000.tar.gz(r-4.5-noble)fmcmc_0.5-2.9000.tar.gz(r-4.4-noble)
fmcmc_0.5-2.9000.tgz(r-4.4-emscripten)fmcmc_0.5-2.9000.tgz(r-4.3-emscripten)
fmcmc.pdf |fmcmc.html✨
fmcmc/json (API)
NEWS
| # Install 'fmcmc' in R: |
| install.packages('fmcmc', repos = c('https://uscbiostats.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/uscbiostats/fmcmc/issues
- lifeexpect - Life expectancy in the US
adaptivebayesian-inferencemarkov-chain-monte-carlomcmcmetropolis-hastingsparallel-computing
Last updated 1 years agofrom:64249ad08b. Checks:OK: 1 ERROR: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 11 2024 |
| R-4.5-win | ERROR | Nov 11 2024 |
| R-4.5-linux | ERROR | Nov 11 2024 |
| R-4.4-win | ERROR | Nov 11 2024 |
| R-4.4-mac | ERROR | Nov 11 2024 |
| R-4.3-win | ERROR | Nov 11 2024 |
| R-4.3-mac | ERROR | Nov 11 2024 |
Exports:append_chainscheck_initialconvergence_autoconvergence_data_getconvergence_data_setconvergence_gelmanconvergence_gewekeconvergence_heildelconvergence_msg_getconvergence_msg_setcov_recursiveget_get_burninget_chain_idget_clget_conv_checkerget_drawsget_elapsedget_funget_initialget_kernelget_logpostget_multicoreget_nchainsget_nstepsget_progressget_seedget_thinget_userdataith_stepkernel_adaptkernel_amkernel_newkernel_nmirrorkernel_normalkernel_normal_reflectivekernel_ramkernel_umirrorkernel_unifkernel_unif_reflectivelast_LAST_CONV_CHECKlast_conv_checkerlast_elapsedlast_kernelLAST_MCMClast_nchainslast_nstepsMCMCMCMC_OUTPUTMCMC_without_conv_checkermean_recursivenew_progress_barplan_update_sequencereflect_on_boundariesset_userdata
Advanced features
Rendered fromadvanced-features.Rmdusingknitr::rmarkdownon Nov 11 2024.Last update: 2021-11-01
Started: 2021-07-20
User-defined kernels
Rendered fromuser-defined-kernels.Rmdusingknitr::rmarkdownon Nov 11 2024.Last update: 2021-07-20
Started: 2019-08-13
Workflow with fmcmc
Rendered fromworkflow-with-fmcmc.Rmdusingknitr::rmarkdownon Nov 11 2024.Last update: 2021-07-21
Started: 2019-08-13
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Append MCMC chains (objects of class coda::mcmc) | append_chains |
| Checks the initial values of the MCMC | check_initial |
| Convergence Monitoring | automatic-stop convergence-checker convergence_auto convergence_data_get convergence_data_set convergence_gelman convergence_geweke convergence_heildel convergence_msg_get convergence_msg_set LAST_CONV_CHECK |
| Recursive algorithms for computing variance and mean | cov_recursive mean_recursive |
| A friendly MCMC framework | fmcmc-package fmcmc |
| Deprecated methods in fmcmc | fmcmc-deprecated last_ last_conv_checker last_elapsed last_kernel LAST_MCMC last_nchains last_nsteps |
| Adaptive Metropolis (AM) Transition Kernel | kernel_adapt kernel_am |
| Mirror Transition Kernels | kernel_mirror kernel_nmirror kernel_umirror |
| Transition Kernels for MCMC | fmcmc_kernel kernels kernel_new |
| Gaussian Transition Kernel | kernel_normal kernel_normal_reflective |
| Robust Adaptive Metropolis (RAM) Transition Kernel | kernel_ram |
| Uniform Transition Kernel | kernel_unif kernel_unif_reflective |
| Life expectancy in the US (2020) | lifeexpect |
| Markov Chain Monte Carlo | MCMC MCMC_OUTPUT MCMC_without_conv_checker Metropolis-Hastings |
| Functions to interact with the main loop | get_userdata ith_step mcmc-loop set_userdata |
| Information about the last 'MCMC' call | get_ get_burnin get_chain_id get_cl get_conv_checker get_draws get_elapsed get_fun get_initial get_kernel get_logpost get_multicore get_nchains get_nsteps get_progress get_seed get_thin mcmc-output |
| Progress bar | new_progress_bar |
| Parameters' update sequence | plan_update_sequence |
| Reflective Boundaries | reflect_on_boundaries |
