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BCT
Bayesian Context Trees for Discrete Time Series
View on CRAN: Click
here
Download and install BCT package within the R console
Install from CRAN:
install.packages("BCT")
Install from Github:
library("remotes")
install_github("cran/BCT") Install by package version:
library("remotes")
install_version("BCT", "1.2") Attach the package and use:
library("BCT")
Maintained by
Valentinian Mihai Lungu
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-11-23
Latest Update: 2022-05-12
Description:
An implementation of a collection of tools for exact Bayesian inference with discrete times series. This package contains functions that can be used for prediction, model selection, estimation, segmentation/change-point detection and other statistical tasks. Specifically, the functions provided can be used for the exact computation of the prior predictive likelihood of the data, for the identification of the a posteriori most likely (MAP) variable-memory Markov models, for calculating the exact posterior probabilities and the AIC and BIC scores of these models, for prediction with respect to log-loss and 0-1 loss and segmentation/change-point detection. Example data sets from finance, genetics, animal communication and meteorology are also provided. Detailed descriptions of the underlying theory and algorithms can be found in [Kontoyiannis et al. 'Bayesian Context Trees: Modelling and exact inference for discrete time series.' Journal of the Royal Statistical Society: Series B (Statistical Methodology), April 2022. Available at: [stat.ME], July 2020] and [Lungu et al. 'Change-point Detection and Segmentation of Discrete Data using Bayesian Context Trees' [stat.ME], March 2022].
How to cite:
Valentinian Mihai Lungu (2020). BCT: Bayesian Context Trees for Discrete Time Series. R package version 1.2, https://cran.r-project.org/web/packages/BCT. Accessed 25 Jun. 2026.
Previous versions and publish date:
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Complete documentation for BCT
Functions, R codes and Examples using
the BCT R package
Some associated functions: BCT . CTW . MAP_parameters . ML . SP500 . calculate_exact_changepoint_posterior . compute_counts . draw_models . el_nino . enterophage . gene_s . generate_data . infer_fixed_changepoints . infer_unknown_changepoints . kBCT . log_loss . pewee . plot_changepoint_posterior . plot_individual_changepoint_posterior . prediction . sars_cov_2 . show_tree . simian_40 . three_changes . zero_one_loss .
Some associated R codes: RcppExports.R . SARS-CoV-2.R . el_nino.R . enterophage.R . gene_s.R . pewee.R . process_bct.R . segmentation_fixed_number_changepoints.R . segmentation_unknown_number_changepoints.R . segmentation_useful_functions.R . simian_40.R . sp500.R . three_changes.R . Full BCT package functions and examples
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