Package: beast
Type: Package
Title: Bayesian Estimation of Change-Points in the Slope of
        Multivariate Time-Series
Version: 1.2
Date: 2026-02-04
Authors@R: 
    c(person(given = "Panagiotis",
             family = "Papastamoulis",
             email = "papapast@yahoo.gr",
             role = c( "aut", "cre"),
             comment = c(ORCID = "0000-0001-9468-7613")))
Maintainer: Panagiotis Papastamoulis <papapast@yahoo.gr>
Description: Assume that a temporal process is composed of contiguous segments with differing slopes and replicated noise-corrupted time series measurements are observed. The unknown mean of the data generating process is modelled as a piecewise linear function of time with an unknown number of change-points. The package infers the joint posterior distribution of the number and position of change-points as well as the unknown mean parameters per time-series by MCMC sampling. A-priori, the proposed model uses an overfitting number of mean parameters but, conditionally on a set of change-points, only a subset of them influences the likelihood. An exponentially decreasing prior distribution on the number of change-points gives rise to a posterior distribution concentrating on sparse representations of the underlying sequence, but also available is the Poisson distribution. See Papastamoulis et al (2019) <doi:10.1515/ijb-2018-0052> for a detailed presentation of the method.
License: GPL-2
Imports: RColorBrewer
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2026-02-04 08:17:55 UTC; panos
Author: Panagiotis Papastamoulis [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-9468-7613>)
Repository: CRAN
Date/Publication: 2026-02-04 08:50:02 UTC
Built: R 4.6.0; ; 2026-04-26 12:41:36 UTC; unix
