prep_proposal_dist: Pre-calculate the change point proposal distribution for the...
In weecology/LDATS: Latent Dirichlet Allocation Coupled with Time Series Analyses

Description Usage Arguments Value Examples

Calculate the proposal distribution in advance of actually running the ptMCMC algorithm in order to decrease computation time. The proposal distribution is a joint of three distributions: [1] a multinomial distribution selecting among the change points within the chain, [2] a binomial distribution selecting the direction of the step of the change point (earlier or later in the time series), and [3] a geometric distribution selecting the magnitude of the step.

1	prep_proposal_dist(nchangepoints, control = list())

`nchangepoints`	Integer corresponding to the number of change points to include in the model. 0 is a valid input (corresponding to no change points, so a singular time series model), and the current implementation can reasonably include up to 6 change points. The number of change points is used to dictate the segmentation of the data for each continuous model and each LDA model.
`control`	A `list` of parameters to control the fitting of the Time Series model including the parallel tempering Markov Chain Monte Carlo (ptMCMC) controls. Values not input assume defaults set by `TS_control`. Currently relevant here is `magnitude`, which controls the magnitude of the step size (is the average of the geometric distribution).

list of two matrix elements: [1] the size of the proposed step for each iteration of each chain and [2] the identity of the change point location to be shifted by the step for each iteration of each chain.