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BayesCPclust  

A Bayesian Approach for Clustering Constant-Wise Change-Point Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BayesCPclust", "0.1.0")



Attach the package and use:
library("BayesCPclust")
Maintained by
Ana Carolina da Cruz
[Scholar Profile | Author Map]
First Published: 2025-01-29
Latest Update: 2025-01-29
Description:
A Gibbs sampler algorithm was developed to estimate change points in constant-wise data sequences while performing clustering simultaneously. The algorithm is described in da Cruz, A. C. and de Souza, C. P. E "A Bayesian Approach for Clustering Constant-wise Change-point Data" <doi:10.48550/arXiv.2305.17631>.
How to cite:
Ana Carolina da Cruz (2025). BayesCPclust: A Bayesian Approach for Clustering Constant-Wise Change-Point Data. R package version 0.1.0, https://cran.r-project.org/web/packages/BayesCPclust. Accessed 02 Apr. 2025.
Previous versions and publish date:
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Complete documentation for BayesCPclust
Functions, R codes and Examples using the BayesCPclust R package
Full BayesCPclust package functions and examples
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