ptmc_discrete_func.RdThis function runs the Parallel Tempering Monte Carlo (PTMC) simulation for a discrete model. It
checks and validates the settings, and if the parameter list is empty, it initializes the parameters
with default values. The function then calls the get_discrete_output function to perform the actual
simulation and return the results.
ptmc_discrete_func(model, data, settings, par = NULL)A list representing the model, which contains necessary information for running the PTMC. This could include the model structure, parameter names, and other model-specific settings.
A list containing the data required for running the model. This might include observed data, priors, or any other inputs that the model requires to perform the simulation.
A list of settings for the PTMC simulation. The list must include the following:
numberChainRuns: The number of chains to run in parallel.
Other settings relevant for running the PTMC simulation, which will be validated using the
check_settings_discete function.
(Optional) A list of parameters for the chains. If provided, each element should correspond to the parameters for one chain. If not provided (or empty), default parameters will be used.
A list containing the results of the PTMC simulation. The structure of the returned list will
depend on the result of the get_discrete_output function, which includes:
mcmc: An MCMC object with posterior samples of the model parameters.
discrete: A list of discrete states generated during the simulation for each chain.
lpost: A data frame of log-posterior values, with columns representing different chains
and rows representing samples.
temp: A data frame of temperatures for each chain at each sample.
acc: A data frame of acceptance rates for each chain at each sample.
outPTpar: A list containing the parameter values for each chain.