# Non-Parametric Bayesian Analyses of Animal Movement

## Documentation for package ‘bayesmove’ version 0.2.1

- DESCRIPTION file.
- Package NEWS.

## Help Pages

assign_behavior | Assign behavior estimates to observations
assign_tseg | Add segment numbers to observations
assign_tseg_internal | Internal function that adds segment numbers to observations
behav_gibbs_sampler | Internal function that runs RJMCMC on a single animal ID
behav_seg_image | Internal function that transforms a vector of bin numbers to a presence-absence matrix
cluster_obs | Cluster observations into behavioral states
cluster_segments | Cluster time segments into behavioral states
CumSumInv | Internal function that calculates the inverted cumsum
df_to_list | Convert data frame to a list by animal ID
discrete_move_var | Discretize movement variables
expand_behavior | Expand behavior estimates from track segments to observations
extract_prop | Extract behavior proportion estimates for each track segment
filter_time | Filter observations for time interval of interest
find_breaks | Find changes for integer variable
get.llk.mixmod | Internal function to calculate the log-likelihood for iteration of mixture model
get.theta | Internal function to calculate theta parameter
get_behav_hist | Extract bin estimates from Latent Dirichlet Allocation or mixture model
get_breakpts | Extract breakpoints for each animal ID
get_MAP | Find the maximum a posteriori (MAP) estimate of the MCMC chain
get_MAP_internal | Internal function to find the maximum a posteriori (MAP) estimate of the MCMC chain
get_summary_stats | Internal function that calculates the sufficient statistics for the segmentation model
insert_NAs | Insert NA gaps to regularize a time series
log_marg_likel | Internal function that calculates the log marginal likelihood of each model being compared
plot_breakpoints | Plot breakpoints over a time series of each movement variable
plot_breakpoints_behav | Internal function for plotting breakpoints over each of the data streams
prep_data | Calculate step lengths, turning angles, net-squared displacement, and time steps
prep_data_internal | Internal function to calculate step lengths, turning angles, and time steps
rmultinom1 | Internal function that samples z's from a categorical distribution
rmultinom2 | Internal function that samples z's from a multinomial distribution
round_track_time | Round time to nearest interval
sample.gamma.mixmod | Internal function to sample the gamma hyperparameter
sample.phi | Internal function to sample bin estimates for each movement variable
sample.phi.mixmod | Internal function to sample bin estimates for each movement variable
sample.v | Internal function to sample parameter for truncated stick-breaking prior
sample.v.mixmod | Internal function to sample parameter for truncated stick-breaking prior
sample.z | Internal function to sample latent clusters
sample.z.mixmod | Internal function to sample latent clusters (for observations)
SampleZAgg | Internal function that samples z1 aggregate
samp_move | Internal function for the Gibbs sampler within the reversible-jump MCMC algorithm
segment_behavior | Segmentation model to estimate breakpoints
shiny_tracks | Dynamically explore tracks within Shiny app
StoreZ | This function helps store z from all iterations after burn in
summarize1 | Internal function that summarizes bin distributions of track segments
SummarizeDat | Internal function that generates nmat matrix to help with multinomial draws
summarize_tsegs | Summarize observations within bins per track segment
traceplot | View trace-plots of output from Bayesian segmentation model
tracks | Simulated set of three tracks.
tracks.list | Tracks discretized and prepared for segmentation.
tracks.seg | Segmented tracks for all IDs.