R package cpm: Sequential and Batch Change Detection Using Parametric and Nonparametric Methods. Sequential and batch change detection for univariate data streams, using the change point model framework. Functions are provided to allow nonparametric distribution-free change detection in the mean, variance, or general distribution of a given sequence of observations. Parametric change detection methods are also provided for Gaussian, Bernoulli and Exponential sequences. Both the batch (Phase I) and sequential (Phase II) settings are supported, and the sequences may contain either a single or multiple change points.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Charles Truong, Laurent Oudre, Nicolas Vayatis: ruptures: change point detection in Python (2018) arXiv
- Mukherjee, Partha Sarathi: On phase II monitoring of the probability distributions of univariate continuous processes (2016)
- Alippi, Cesare; Boracchi, Giacomo; Roveri, Manuel: Ensembles of change-point methods to estimate the change point in residual sequences (2013) ioport
- Nicholas A. James, David S. Matteson: ecp: An R Package for Nonparametric Multiple Change Point Analysis of Multivariate Data (2013) arXiv