BCT

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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", "1.3")

Attach the package and use:

 library("BCT")

Maintained by
Valentinian Mihai Lungu
[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 1.3, https://cran.r-project.org/web/packages/BCT. Accessed 30 Oct. 2026.

Previous versions and publish date:

1.0 (2020-11-23 10:20), 1.1 (2020-12-07 23:30), 1.2 (2022-05-12 16:00), (2026-07-09 07:57)

Other packages that cited BCT R package

View BCT citation profile

Other R packages that BCT depends, imports, suggests or enhances

View BCT dependency map

Complete documentation for BCT

View documentation PDF

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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