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

# No-U-Turn MCMC Sampling for 'ADMB' Models

## Documentation for package ‘adnuts’ version 1.1.2

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

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