Package: adnuts 1.1.3

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_1.1.3.tar.gz
adnuts_1.1.3.zip(r-4.7)adnuts_1.1.3.zip(r-4.6)adnuts_1.1.3.zip(r-4.5)
adnuts_1.1.3.tgz(r-4.6-any)adnuts_1.1.3.tgz(r-4.5-any)
adnuts_1.1.3.tar.gz(r-4.7-any)adnuts_1.1.3.tar.gz(r-4.6-any)
adnuts_1.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
adnuts/json (API)

# Install 'adnuts' in R:

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

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

Pkgdown/docs site:https://cole-monnahan-noaa.github.io

On CRAN:

6.59 score 25 stars 103 scripts 385 downloads 1 mentions 15 exports 53 dependencies

Last updated from:c401649b84. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	240
source / vignettes	OK	269
linux-release-x86_64	OK	246
macos-release-arm64	OK	175
macos-oldrel-arm64	OK	308
windows-devel	OK	219
windows-release	OK	179
windows-oldrel	OK	192
wasm-release	OK	190

Exports:adfit check_identifiable extract_sampler_params extract_samples is.adfit launch_shinyadmb pairs_admb plot_marginals plot_sampler_params plot_uncertainties sample_admb sample_inits sample_nuts sample_rwm sample_tmb

Dependencies:abind backports BH callr checkmate cli coda cpp11 desc distributional ellipse farver generics ggplot2 glue gridExtra gtable inline isoband labeling lattice lifecycle loo magrittr matrixStats numDeriv otel pillar pkgbuild pkgconfig posterior processx ps QuickJSR R2admb R6 RColorBrewer Rcpp RcppEigen RcppParallel rlang rstan S7 scales snow snowfall StanHeaders tensorA tibble utf8 vctrs viridisLite withr

No-U-turn sampling for ADMB models

Rendered fromadnuts.Rmdusingknitr::rmarkdown

Last update: 2026-04-03
Started: 2017-12-03

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
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) class	adfit
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 Hessian	check_identifiable
Extract sampler parameters from a fit.	extract_sampler_params
Extract posterior samples from a model fit.	extract_samples
Check object of class adfit	is.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 model	plot_marginals
Plot adaptation metrics for a fitted model.	plot_sampler_params
Plot MLE vs MCMC marginal standard deviations for each parameter	plot_uncertainties
Plot object of class adfit	plot.adfit
Print summary of adfit object	print.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 adnuts	sample_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 adfit	summary.adfit