Bayesian Context Trees for Discrete Time Series

Documentation for package ‘BCT’ version 1.2

BCT	Bayesian Context Trees (BCT) algorithm
calculate_exact_changepoint_posterior	Calculates the exact posterior for a sequence with a single change-point.
compute_counts	Compute empirical frequencies of all contexts
CTW	Context Tree Weighting (CTW) algorithm
draw_models	Plot the results of the BCT and kBCT functions
el_nino	El Nino
enterophage	Enterobacteria_phage_lambda
generate_data	Sequence generator
gene_s	SARS-CoV-2 gene S
infer_fixed_changepoints	Inferring the change-points locations when the number of change-points is fixed.
infer_unknown_changepoints	Inferring the number of change-points and their locations.
kBCT	k-Bayesian Context Trees (kBCT) algorithm
log_loss	Calculating the log-loss incurred in prediction
MAP_parameters	Parameters of the MAP model
ML	Maximum Likelihood
pewee	Pewee birdsong
plot_changepoint_posterior	Plot the empirical posterior distribution of the change-points.
plot_individual_changepoint_posterior	Plot empirical conditional posterior of the number of change-points.
prediction	Prediction
sars_cov_2	SARS-CoV-2 genome
show_tree	Plot tree with given contexts
simian_40	simian_40
SP500	Daily changes in the S&P 500 index
three_changes	three_changes
zero_one_loss	Calculating the 0-1 loss incurred in prediction