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. |

max.time |
numeric. The number of of the last observation of `dat` . |

dat |
A matrix that only contains columns storing discretized data for
each of the movement variables used within `get_summary_stats` . |

alpha |
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. |

nbins |
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` . |

ndata.types |
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.