Package: ccid
Type: Package
Title: Cross-Covariance Isolate Detect: a New Change-Point Method for
        Estimating Dynamic Functional Connectivity
Version: 1.0.0
Depends: R (>= 3.6.0)
Imports: IDetect, hdbinseg, GeneNet, gdata
Authors@R: c(person("Andreas", "Anastasiou", email = "anastasiou.andreas@ucy.ac.cy", role = c("aut", "cre")),
        person("Ivor", "Cribben", email = "cribben@ualberta.ca", role = "aut"),
        person("Piotr", "Fryzlewicz", email = "p.fryzlewicz@lse.ac.uk", role = "aut"))
Description: 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) <doi:10.1101/2020.12.20.423696>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/Anastasiou-Andreas/ccid
BugReports: https://github.com/Anastasiou-Andreas/ccid/issues
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-01-05 11:11:56 UTC; ANASTAS7
Author: Andreas Anastasiou [aut, cre],
  Ivor Cribben [aut],
  Piotr Fryzlewicz [aut]
Maintainer: Andreas Anastasiou <anastasiou.andreas@ucy.ac.cy>
Repository: CRAN
Date/Publication: 2021-01-07 11:20:09 UTC
