Package: adnuts 1.1.2

Cole Monnahan

adnuts: No-U-Turn MCMC Sampling for 'ADMB' Models

Bayesian inference using the no-U-turn (NUTS) algorithm by Hoffman and Gelman (2014) <https://www.jmlr.org/papers/v15/hoffman14a.html>. Designed for 'AD Model Builder' ('ADMB') models, or when R functions for log-density and log-density gradient are available, such as 'Template Model Builder' models and other special cases. Functionality is similar to 'Stan', and the 'rstan' and 'shinystan' packages are used for diagnostics and inference.

Authors:Cole Monnahan [aut, cre]

adnuts_1.1.2.tar.gz
adnuts_1.1.2.zip(r-4.5)adnuts_1.1.2.zip(r-4.4)adnuts_1.1.2.zip(r-4.3)
adnuts_1.1.2.tgz(r-4.4-any)adnuts_1.1.2.tgz(r-4.3-any)
adnuts_1.1.2.tar.gz(r-4.5-noble)adnuts_1.1.2.tar.gz(r-4.4-noble)
adnuts_1.1.2.tgz(r-4.4-emscripten)adnuts_1.1.2.tgz(r-4.3-emscripten)
adnuts.pdf |adnuts.html✨
adnuts/json (API)
NEWS

# Install 'adnuts' in R:
install.packages('adnuts', repos = c('https://cole-monnahan-noaa.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/cole-monnahan-noaa/adnuts/issues

On CRAN:

15 exports 23 stars 2.44 score 57 dependencies 1 mentions 50 scripts 354 downloads

Last updated 8 months agofrom:ff0c8d3d56. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 30 2024
R-4.5-winOKAug 30 2024
R-4.5-linuxOKAug 30 2024
R-4.4-winOKAug 30 2024
R-4.4-macOKAug 30 2024
R-4.3-winOKAug 30 2024
R-4.3-macOKAug 30 2024

Exports:adfitcheck_identifiableextract_sampler_paramsextract_samplesis.adfitlaunch_shinyadmbpairs_admbplot_marginalsplot_sampler_paramsplot_uncertaintiessample_admbsample_initssample_nutssample_rwmsample_tmb

Dependencies:abindbackportsBHcallrcheckmateclicodacolorspacedescdistributionalellipsefansifarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR2admbR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanscalessnowsnowfallStanHeaderstensorAtibbleutf8vctrsviridisLitewithr

No-U-turn sampling for ADMB models

Cole C. Monnahan

Rendered fromadnuts.Rmdusingknitr::rmarkdownon Aug 30 2024.

Last update: 2021-03-02
Started: 2017-12-03

Readme and manuals

Help Manual

Help pageTopics
Check that the model is compiled with the right version of ADMB which is 12.0 or later.check_ADMB_version
Check if the session is interactive or Rstudio which has implications for parallel output.check_console_printing
Check that the file can be found.check_model_path
Read in admodel.hes file.getADMBHessian
Hidden wrapper function for sampling from ADMB models.sample_admb
Convert model name depending on system.update_model
Constructor for the "adfit" (A-D fit) classadfit
adnuts: No-U-turn sampling for AD Model Builder (ADMB)adnuts
Convert object of class adfit to data.frame. Calls 'extract_samples'as.data.frame.adfit
Check identifiability from model Hessiancheck_identifiable
Extract sampler parameters from a fit.extract_sampler_params
Extract posterior samples from a model fit.extract_samples
Check object of class adfitis.adfit
Launch shinystan for an ADMB fit.launch_shinyadmb
Launch shinystan for a TMB fit.launch_shinytmb
Plot pairwise parameter posteriors and optionally the MLE points and confidence ellipses.pairs_admb
Plot marginal distributions for a fitted modelplot_marginals
Plot adaptation metrics for a fitted model.plot_sampler_params
Plot MLE vs MCMC marginal standard deviations for each parameterplot_uncertainties
Plot object of class adfitplot.adfit
Print summary of adfit objectprint.adfit
Deprecated version of wrapper function. Use sample_nuts or sample_rwm instead.sample_admb
Function to generate random initial values from a previous fit using adnutssample_inits
Bayesian inference of an ADMB model using the no-U-turn sampler (NUTS) or random walk Metropolis (RWM) algorithms.sample_nuts sample_rwm wrappers
Bayesian inference of a TMB model using the no-U-turn sampler.sample_tmb
Draw MCMC samples from a model posterior using a static HMC sampler.sample_tmb_hmc
Draw MCMC samples from a model posterior using the No-U-Turn (NUTS) sampler with dual averaging.sample_tmb_nuts
[Deprecated] Draw MCMC samples from a model posterior using a Random Walk Metropolis (RWM) sampler.sample_tmb_rwm
Print summary of object of class adfitsummary.adfit