Bayesian Context Trees for Discrete Time Series

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Documentation for package ‘BCT’ version 1.2

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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