Package: monty 0.2.36

Rich FitzJohn

monty: Monte Carlo Models

Experimental sources for the next generation of mcstate, now called 'monty', which will support much of the old mcstate functionality but new things like better parameter interfaces, Hamiltonian Monte Carlo, and other features.

Authors:Rich FitzJohn [aut, cre], Wes Hinsley [aut], Ed Knock [aut], Marc Baguelin [aut], Imperial College of Science, Technology and Medicine [cph]

monty_0.2.36.tar.gz
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monty.pdf |monty.html
monty/json (API)

# Install 'monty' in R:
install.packages('monty', repos = c('https://mrc-ide.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/mrc-ide/monty/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

6.70 score 2 stars 2 packages 19 scripts 40 exports 4 dependencies

Last updated 8 hours agofrom:aa11bb2a15 (on main). Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-win-x86_64OKNov 06 2024
R-4.5-linux-x86_64OKNov 06 2024
R-4.4-win-x86_64OKNov 06 2024
R-4.4-mac-x86_64OKNov 06 2024
R-4.4-mac-aarch64OKNov 06 2024
R-4.3-win-x86_64OKNov 06 2024
R-4.3-mac-x86_64OKNov 06 2024
R-4.3-mac-aarch64OKNov 06 2024

Exports:monty_differentiationmonty_domain_expandmonty_dslmonty_dsl_distributionsmonty_dsl_error_explainmonty_dsl_parse_distributionmonty_examplemonty_modelmonty_model_combinemonty_model_densitymonty_model_direct_samplemonty_model_functionmonty_model_gradientmonty_model_propertiesmonty_observermonty_packermonty_packer_groupedmonty_rngmonty_rng_distributed_pointermonty_rng_distributed_statemonty_rng_pointermonty_runner_callrmonty_runner_parallelmonty_runner_serialmonty_runner_simultaneousmonty_samplemonty_sample_continuemonty_sample_manual_cleanupmonty_sample_manual_collectmonty_sample_manual_infomonty_sample_manual_preparemonty_sample_manual_prepare_continuemonty_sample_manual_runmonty_sampler_adaptivemonty_sampler_hmcmonty_sampler_nested_adaptivemonty_sampler_nested_random_walkmonty_sampler_random_walkmonty_samples_thinwith_trace_random

Dependencies:clicpp11R6rlang

DSL parse errors

Rendered fromdsl-errors.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2024-10-10
Started: 2024-08-06

Introduction to monty

Rendered frommonty.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2024-10-02
Started: 2024-08-21

Probabilistic DSL

Rendered fromdsl.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2024-10-10
Started: 2024-08-05

Samplers

Rendered fromsamplers.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2024-10-02
Started: 2024-03-08

Working with samples

Rendered fromsamples.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2024-08-21
Started: 2024-08-16

Readme and manuals

Help Manual

Help pageTopics
Differentiate expressionsmonty_differentiation
Expand (and check) domain against a packermonty_domain_expand
Domain Specific Language for montymonty_dsl
Information about supported distributionsmonty_dsl_distributions
Explain monty errormonty_dsl_error_explain
Parse distribution expressionmonty_dsl_parse_distribution
Example modelsmonty_example
Create basic modelmonty_model
Combine two modelsmonty_model_combine
Compute log densitymonty_model_density
Directly sample from a modelmonty_model_direct_sample
Create 'monty_model' from a function computing densitymonty_model_function
Compute gradient of log densitymonty_model_gradient
Describe model propertiesmonty_model_properties
Create observermonty_observer
Build a packermonty_packer
Build a nested packermonty_packer_grouped
Monty Random Number Generatormonty_rng
Create a set of distributed seedsmonty_rng_distributed_pointer monty_rng_distributed_state
Create pointer to random number generator streammonty_rng_pointer
Run MCMC chains in parallel with 'callr'monty_runner_callr
Run MCMC chain in parallelmonty_runner_parallel
Run MCMC chain in seriesmonty_runner_serial
Run MCMC chains simultaneouslymonty_runner_simultaneous
Sample from a modelmonty_sample
Continue samplingmonty_sample_continue
Clean up samplesmonty_sample_manual_cleanup
Collect manually run samplesmonty_sample_manual_collect
Get information about manually scheduled samplesmonty_sample_manual_info
Prepare to sample with manual schedulingmonty_sample_manual_prepare
Prepare to continue sampling with manual schedulingmonty_sample_manual_prepare_continue
Run sample with manual schedulingmonty_sample_manual_run
Adaptive Metropolis-Hastings Samplermonty_sampler_adaptive
Create HMCmonty_sampler_hmc
Nested Adaptive Metropolis-Hastings Samplermonty_sampler_nested_adaptive
Nested Random Walk Samplermonty_sampler_nested_random_walk
Random Walk Samplermonty_sampler_random_walk
Thin samplesmonty_samples_thin
Trace random number callswith_trace_random