This algorithm allows breakpoint detections for changes in variation assuming that the variance function can be described by a piecewise constant function with segments delimited by unknown change-points. The approach is a generalization of the cumSeg procedure proposed by Muggeo and Adelfio (2011) assuming that testing for stepwise changes in variance of a sequence of Gaussian random variables may be transformed equivalently to the case of testing for changes in mean of the squared residuals (from an estimated linear model that accounts for the mean behavior of the observed signal) assuming a gamma GLM with a log-link function. A variation of lars procedure adapted to the GLM case is considered to discard the spurious change-points on the basis of a generalized version of the BIC. The proposed approach results in a very efficient algorithm even with n large and many change-points to be estimated. Adelfio, G. (2012), Change-point detection for variance piecewise constant models, Communications in Statistics, Simulation and Computation, 41:4, 437-448. Muggeo, V.M.R., Adelfio, G. (2011) Efficient change point detection for genomic sequences of continuous measurements, Bioinformatics 27, 161-166.
Giada Adelfio
Maintainer: Gianluca Sottile <gianluca.sottile@unipa.it>
| Package: | jumpointsVar |
| Type: | Package |
| Version: | 0.1.0 |
| Date: | 2018-01-18 |
| License: | GPL-2 |
The function jumpointsVar allows to specify the variable in which to look for change-point in variance. The auxiliary function plot.jumpointsVar can be used to plot the brekpoints detected from the main algorithm.
Adelfio, G. (2012), Change-point detection for variance piecewise constant models, Communications in Statistics, Simulation and Computation, 41:4, 437-448
Muggeo, V.M.R., Adelfio, G. (2011) Efficient change point detection for genomic sequences of continuous measurements, Bioinformatics 27, 161-166.
##---- see jumpointsVar documentation ----
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