Non-Parametric Bayesian Analyses of Animal Movement

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Documentation for package ‘bayesmove’ version 0.2.1

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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.