This is RJMCMC algorithm that drives the proposal and selection of breakpoints for the data based on the difference in log marginal likelihood. This function is called within behav_gibbs_sampler.

samp_move(breakpt, max.time, dat, alpha, nbins, ndata.types)

## Arguments

breakpt numeric. A vector of breakpoints. numeric. The number of of the last observation of dat. A matrix that only contains columns storing discretized data for each of the movement variables used within get_summary_stats. numeric. A single value used to specify the hyperparameter for the prior distribution. A standard value for alpha is typically 1, which corresponds with a vague prior on the Dirichlet distribution. numeric. A vector of the number of bins used to discretize each movement variable. These must be in the same order as the columns within dat. numeric. The length of nbins.

## Value

The breakpoints and log marginal likelihood are retained from the selected model from the Gibbs sampler and returned as elements of a list. This is performed for each iteration of the MCMC algorithm.