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bacontrees  

Bayesian Context Trees for Discrete Sequence Data
View on CRAN: Click here


Download and install bacontrees package within the R console
Install from CRAN:
install.packages("bacontrees")

Install from Github:
library("remotes")
install_github("cran/bacontrees")

Install by package version:
library("remotes")
install_version("bacontrees", "1.0.0")



Attach the package and use:
library("bacontrees")
Maintained by
Victor Freguglia
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-05-12
Latest Update: 2026-05-12
Description:
Models discrete sequential data using Bayesian Context Trees. Context trees, also known as Variable Length Markov Chains (VLMCs), are parsimonious Markov models where the order of dependence can vary with the observed past. Provides a generic 'R6' class structure that exposes the full tree for building custom algorithms, exact Bayesian inference via a bottom-up recursive algorithm (closed-form marginal likelihood, Maximum A Posteriori (MAP) tree, exact posterior probabilities, and exact sampling from the posterior), a frequentist estimator via the context algorithm with likelihood-ratio pruning, simulation utilities, and a Metropolis-Hastings sampler. See Paulichen and Freguglia (2026) <doi:10.48550/arXiv.2603.25806>.
How to cite:
Victor Freguglia (2026). bacontrees: Bayesian Context Trees for Discrete Sequence Data. R package version 1.0.0, https://cran.r-project.org/web/packages/bacontrees. Accessed 24 Oct. 2026.
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