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fastOnlineCpt (version 1.0)

Online Multivariate Changepoint Detection

Description

Implementation of a simple algorithm designed for online multivariate changepoint detection of a mean in sparse changepoint settings. The algorithm is based on a modified cusum statistic and guarantees control of the type I error on any false discoveries, while featuring O(1) time and O(1) memory updates per series as well as a proven detection delay.

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Version

Install

install.packages('fastOnlineCpt')

Monthly Downloads

162

Version

1.0

License

GPL (>= 2)

Maintainer

Georg Hahn

Last Published

July 9th, 2021

Functions in fastOnlineCpt (1.0)

Test if a changepoint has occurred.

Reset the algorithm in order to detect a new changepoint. The algorithm can be reset at any point in time. To ensure valid multiple testing corrections, the time horizon is not reset to zero.

Initialize a new object of the class "fastOnlineCpt". This object allows one to add data in an online fashion and test for a changepoint.

Add new \(p\)-dimensional data point, where \(p\) is the number of time series being monitored.

Return the last result of the changepoint test performed with the function "checkCpt" as a vector.

fastOnlineCpt-class

S4 class providing functionality to detect multivariate changepoints in an online setting.