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| calc_linex_a | estimate optimal 'a' parameter for linex loss function |
| convert.HDS.to.mcmc | function to convert HierarchicalDS MCMC list vector (used in estimation) into an mcmc object (cf. coda package) |
| generate_inits | generate initial values for MCMC chain if not already specified by user |
| generate_inits_misID | generate initial values for misID model if not already specified by user |
| get_confusion_array | Fill confusion array - one confusion matrix for each individual (DEPRECATED) |
| get_confusion_mat | Fill a list with confusion matrices for each record |
| get_mod_matrix | function to produce a design matrix given a dataset and user-specified formula object |
| hierarchical_DS | Primary function for hierarchical, areal analysis of distance sampling data. This function pre-processes data and calls other functions to perform the analysis, and is the only function the user needs to call themselves. |
| linear_adj | Produce an adjacency matrix for a vector |
| log_lambda_gradient | compute the first derivative of log_lambda likelihood component for Langevin-Hastings |
| log_lambda_log_likelihood | compute the likelihood for nu parameters |
| mcmc_ds | Function for MCMC analysis |
| plot_obs_pred | plot 'observed' versus predicted values for abundance of each species at each transect |
| post_loss | function to calculate posterior predictive loss given the output object from hierarchicalDS |
| probit.fct | Mrds probit detection and related functions |
| rrw | SIMULATE AN ICAR PROCESS |
| simdata | MCMC output from running example script in HierarchicalDS |
| simulate_data | function to simulate distance sampling data from simple model with increasing abundance intensity, no assumed spatial structure, and point independence. If no parameters are given, uses internally defined values. |
| square_adj | Produce an adjacency matrix for a square grid |
| stack_data | function to stack data (going from three dimensional array to a two dimensional array including only "existing" animals |
| stack_data_misID | function to stack data for midID updates (going from four dimensional array to a two dimensional array including observed groups |
| summary_N | calculate parameter estimates and confidence intervals for various loss functions |
| switch_pdf | function to calculate the joint pdf for a sample of values from one of a number of pdfs |
| switch_sample | function to sample from a specified probability density function |
| switch_sample_prior | function to sample from hyperpriors of a specified probability density function; note that initial values for sigma of lognormal random effects are fixed to a small value (0.05) to prevent numerical errors |
| table.mcmc | function to export posterior summaries from an mcmc object to a table |