Package index • adnuts

All functions

adfit(): Constructor for the "adfit" (A-D fit) class

as.data.frame(<adfit>): Convert object of class adfit to data.frame. Calls extract_samples

as.tmbfit(): Construtor for tmbfit objects

benchmark_metrics(): Calculate gradient timings on a model for different metrics

check_identifiable(): Check identifiability from model Hessian

.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

.get_inits(): Get a single initial value vector in untransformed model space

.get_inputs(): Prepare inputs for sparse sampling

.get_Q(): Get the joint precision matrix Q from an optimized TMB or RTMB obj.

.get_Qinv(): Get the joint covariance Sigma from an optimized TMB or RTMB obj without random effects.

.make_unique_names(): Function to take a character vector of parameter names and force them to be unique by appending numbers in square brackets as needed

.print.mat.stats(): Print matrix stats

.rotate_posterior(): Update algorithm for mass matrix.

.rotate_space(): Update algorithm for mass matrix.

.sample_admb(): Hidden wrapper function for sampling from ADMB models

.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.

get_post(): Extract posterior samples from a tmbfit object

is.adfit(): Check object of class adfit

launch_shinyadmb(): Launch shinystan for an ADMB fit.

launch_shinytmb(): Launch shinystan for a TMB fit.

pairs(<adfit>): Plot pairwise parameter posteriors and optionally the MLE points and confidence ellipses.

pairs_admb(): Deprecated function to make custom pairs plots for 'adfit' objects. Use S3 class method 'pairs' instead, and see ?pairs.adfit for help.

plot(<adfit>): Plot object of class adfit

plot_marginals(): Plot marginal distributions for a fitted model

plot_Q(): Make an image plot showing the correlation (lower triangle) and sparsity (upper triangle).

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_snuts(): NUTS sampling for TMB models using a sparse metric (BETA).

sample_sparse_tmb(): Deprecated version of sample_snuts

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

sample_nuts() sample_rwm(): Bayesian inference of an ADMB model using the no-U-turn sampler (NUTS) or random walk Metropolis (RWM) algorithms.