Identify the MCMC iteration that holds the MAP estimate. This will be used to inform get_breakpts as to which breakpoints should be retained on which to assign track segments to the observations of each animal ID.

get_MAP(dat, nburn)



A data frame where each row holds the log marginal likelihood values at each iteration of the MCMC chain.


numeric. The size of the burn-in phase after which the MAP estimate will be identified.


A numeric vector of iterations at which the MAP estimate was found for each animal ID.


# \donttest{ #load data data(tracks.list) #subset only first track tracks.list<- tracks.list[1] #only retain id and discretized step length (SL) and turning angle (TA) columns tracks.list2<- purrr::map(tracks.list, subset, select = c(id, SL, TA)) set.seed(1) # Define model params alpha<- 1 ngibbs<- 1000 nbins<- c(5,8) #future::plan(future::multisession) #run all MCMC chains in parallel dat.res<- segment_behavior(data = tracks.list2, ngibbs = ngibbs, nbins = nbins, alpha = alpha)
#> 1.326 sec elapsed
# Determine MAP iteration for selecting breakpoints and store breakpoints MAP.est<- get_MAP(dat = dat.res$LML, nburn = ngibbs/2) # }