segMGarch - Multiple Change-Point Detection for High-Dimensional GARCH Processes
Implements a segmentation algorithm for multiple change-point detection in high-dimensional GARCH processes. It simultaneously segments GARCH processes by identifying 'common' change-points, each of which can be shared by a subset or all of the component time series as a change-point in their within-series and/or cross-sectional correlation structure.
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cpp
1.23 score 17 scripts 212 downloadswbsts - Multiple Change-Point Detection for Nonstationary Time Series
Implements detection for the number and locations of the change-points in a time series using the Wild Binary Segmentation and the Locally Stationary Wavelet model of Korkas and Fryzlewicz (2017) <doi:10.5705/ss.202015.0262>.
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cpp
1.23 score 17 scripts 186 downloadseNchange - Ensemble Methods for Multiple Change-Point Detection
Implements a segmentation algorithm for multiple change-point detection in univariate time series using the Ensemble Binary Segmentation of Korkas (2022) <Journal of the Korean Statistical Society, 51(1), pp.65-86.>.
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cpp
1.00 score 1 stars 240 downloads