adnuts1.1.2 package

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

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

dot-check_ADMB_version

Check that the model is compiled with the right version of ADMB which ...

dot-check_console_printing

Check if the session is interactive or Rstudio which has implications ...

dot-check_model_path

Check that the file can be found

dot-getADMBHessian

Read in admodel.hes file

dot-sample_admb

Hidden wrapper function for sampling from ADMB models

dot-update_model

Convert model name depending on system

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 c...

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 ...

sample_inits

Function to generate random initial values from a previous fit using a...

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) sa...

sample_tmb_rwm

[Deprecated] Draw MCMC samples from a model posterior using a Random W...

summary.adfit

Print summary of object of class adfit

wrappers

Bayesian inference of an ADMB model using the no-U-turn sampler (NUTS)...

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.

  • Maintainer: Cole Monnahan
  • License: GPL-3 | file LICENSE
  • Last published: 2021-03-02