samp_move: Internal function for the Gibbs sampler within the...
In bayesmove: Non-Parametric Bayesian Analyses of Animal Movement

View source: R/segmentation_gibbs_functions.R

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.

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

`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`.

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.

bayesmove documentation built on Oct. 22, 2021, 9:08 a.m.