changepoint.geo-package {changepoint.geo}R Documentation

Geometrically Inspired Multivariate Changepoint Detection

Description

Implements the high-dimensional changepoint detection method GeomCP (Grundy et al. 2020) and the related mappings used for changepoint detection. These methods view the changepoint problem from a geometrical viewpoint and aim to extract relevant geometrical features in order to detect changepoints. The geomcp() function should be your first point of call.

Details

Package: changepoint.geo
Type: Package
Title: Geometrically Inspired Multivariate Changepoint Detection
Version: 1.0.1
Date: 2020-03-29
Authors@R: c(person("Thomas","Grundy",role=c("aut","cre"),email="t.grundy1@lancaster.ac.uk"), person("Rebecca","Killick",role="ths"))
Maintainer: Thomas Grundy <t.grundy1@lancaster.ac.uk>
URL: https://github.com/grundy95/changepoint.geo/
Description: Implements the high-dimensional changepoint detection method GeomCP and the related mappings used for changepoint detection. These methods view the changepoint problem from a geometrical viewpoint and aim to extract relevant geometrical features in order to detect changepoints. The geomcp() function should be your first point of call. References: Grundy et al. (2020) <doi:10.1007/s11222-020-09940-y>.
Depends: R(>= 3.6), changepoint, changepoint.np, methods, ggplot2
Imports: Rdpack
RdMacros: Rdpack
Suggests: testthat, MASS
License: GPL
LazyLoad: yes
NeedsCompilation: no
Packaged: 2019-06-18 13:30:22 UTC; grundy
Author: Thomas Grundy [aut, cre], Rebecca Killick [ths]

Author(s)

Thomas Grundy [aut, cre], Rebecca Killick [ths]

Maintainer: Thomas Grundy <t.grundy1@lancaster.ac.uk>

References

Grundy T, Killick R, Mihalyov G (2020). “High-dimensional changepoint detection via a geometrically inspired mapping.” Stat Comput, 0(0). doi: 10.1007/s11222-020-09940-y.

Killick R, Fearnhead P, Eckley IA (2012). “Optimal detection of changepoints with a linear computational cost.” J. Am. Stat. Assoc., 107(500), 1590–1598.

See Also

geomcp

Examples

X <- rbind(matrix(rnorm(100*50),ncol=50),matrix(rnorm(100*50,0,2),ncol=50))
ans <- geomcp(X)
summary(ans)

[Package changepoint.geo version 1.0.1 Index]