bayesmove0.2.1 package

Non-Parametric Bayesian Analyses of Animal Movement

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 presenc...

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 mix...

get.theta

Internal function to calculate theta parameter

get_behav_hist

Extract bin estimates from Latent Dirichlet Allocation or mixture mode...

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 t...

get_summary_stats

Internal function that calculates the sufficient statistics for the se...

insert_NAs

Insert NA gaps to regularize a time series

log_marg_likel

Internal function that calculates the log marginal likelihood of each ...

pipe

Pipe operator

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 strea...

prep_data

Calculate step lengths, turning angles, net-squared displacement, and ...

prep_data_internal

Internal function to calculate step lengths, turning angles, and time ...

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

samp_move

Internal function for the Gibbs sampler within the reversible-jump MCM...

sample.gamma.mixmod

Internal function to sample the gamma hyperparameter

sample.phi.mixmod

Internal function to sample bin estimates for each movement variable

sample.phi

Internal function to sample bin estimates for each movement variable

sample.v.mixmod

Internal function to sample parameter for truncated stick-breaking pri...

sample.v

Internal function to sample parameter for truncated stick-breaking pri...

sample.z.mixmod

Internal function to sample latent clusters (for observations)

sample.z

Internal function to sample latent clusters

SampleZAgg

Internal function that samples z1 aggregate

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

summarize_tsegs

Summarize observations within bins per track segment

summarize1

Internal function that summarizes bin distributions of track segments

SummarizeDat

Internal function that generates nmat matrix to help with multinomial ...

traceplot

View trace-plots of output from Bayesian segmentation model

Methods for assessing animal movement from telemetry and biologging data using non-parametric Bayesian methods. This includes features for pre- processing and analysis of data, as well as the visualization of results from the models. This framework does not rely on standard parametric density functions, which provides flexibility during model fitting. Further details regarding part of this framework can be found in Cullen et al. (2021) <doi:10.1101/2020.11.05.369702>.

  • Maintainer: Joshua Cullen
  • License: GPL-3
  • Last published: 2021-10-22