Simulating, Estimating and Diagnosing MGARCH (BEKK and mGJR)
Processes
c(
person("Harald", "Schmidbauer", email="harald@hs-stat.com", role=c("aut")),
person("Angi", "Roesch", email="angi@angi-stat.com", role=c("aut")),
person("Vehbi Sinan", "Tunalioglu", email="vst@vsthost.com", role=c("cre", "aut")))
Procedures to simulate, estimate and diagnose MGARCH
processes of BEKK and multivariate GJR (bivariate asymmetric GARCH
model) specification.
Harald Schmidbauer [aut],
Angi Roesch [aut],
Vehbi Sinan Tunalioglu [cre, aut]

c(person("Eric", "Bridgeford", role = c("aut", "cre"),
email = "ericwb95@gmail.com"),
person("Censheng", "Shen", role="aut",
email="cshen6@jhu.edu"),
person("Shangsi", "Wang", role = "aut",
email = "swang127@jhu.edu"),
person("Joshua", "Vogelstein", role = "ths",
email = "jovo@jhu.edu"))
Multiscale Graph Correlation (MGC) is a framework developed by Shen et al. (2017) <arXiv:1609.05148> that extends global correlation procedures to be multiscale; consequently, MGC tests typically require far fewer samples than existing methods for a wide variety of dependence structures and dimensionalities, while maintaining computational efficiency. Moreover, MGC provides a simple and elegant multiscale characterization of the potentially complex latent geometry underlying the relationship.
testthat, ggplot2, reshape2, knitr, rmarkdown
Eric Bridgeford [aut, cre],
Censheng Shen [aut],
Shangsi Wang [aut],
Joshua Vogelstein [ths]

Multiscale Graph Correlation (MGC) is a framework developed by Vogelstein et al. (2019) <DOI:10.7554/eLife.41690> that extends global correlation procedures to be multiscale; consequently, MGC tests typically require far fewer samples than existing methods for a wide variety of dependence structures and dimensionalities, while maintaining computational efficiency. Moreover, MGC provides a simple and elegant multiscale characterization of the potentially complex latent geometry underlying the relationship.
stats, MASS, abind, boot, energy, raster
testthat (>= 2.1.0), ggplot2, reshape2, knitr, rmarkdown