R-universe - anastasiou-andreas (Andreas Anastasiou)

ccid - Cross-Covariance Isolate Detect: a New Change-Point Method for Estimating Dynamic Functional Connectivity

Provides efficient implementation of the Cross-Covariance Isolate Detect (CCID) methodology for the estimation of the number and location of multiple change-points in the second-order (cross-covariance or network) structure of multivariate, possibly high-dimensional time series. The method is motivated by the detection of change points in functional connectivity networks for functional magnetic resonance imaging (fMRI), electroencephalography (EEG), magentoencephalography (MEG) and electrocorticography (ECoG) data. The main routines in the package have been extensively tested on fMRI data. For details on the CCID methodology, please see Anastasiou et al (2020).

Last updated

2.70 score 2 scripts 372 downloads

IDetect - Isolate-Detect Method for Multiple Change-Point Detection

The IDetect provides efficient implementation of the ID methodology for the consistent estimation of the number and location of multiple change-points in one-dimensional data sequences from the `deterministic + noise' model. Currently implemented scenarios are: piecewise-constant signal, piecewise-constant signal with a heavy-tailed noise, continuous piecewise-linear signal, continuous piecewise-linear signal with a heavy-tailed noise.

Last updated

1.86 score 1 dependents 24 scripts 430 downloads