gmvarkit: Estimate Gaussian Mixture Vector Autoregressive Model

Unconstrained and constrained maximum likelihood estimation of structural and reduced form Gaussian mixture vector autoregressive (GMVAR) model, quantile residual tests, graphical diagnostics, simulations, forecasting, and estimation of generalized impulse response function. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2016) <doi:10.1016/j.jeconom.2016.02.012>, Savi Virolainen (2020) <arXiv:2007.04713>.

Version: 1.4.1
Depends: R (≥ 3.6.0)
Imports: Brobdingnag (≥ 1.2-4), mvnfast (≥ 0.2.5), parallel (≥ 3.0.0), stats (≥ 3.0.0), pbapply (≥ 1.4-2), graphics (≥ 3.0.0), grDevices (≥ 3.0.0)
Suggests: testthat, knitr, rmarkdown
Published: 2021-01-27
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: gmvarkit results


Reference manual: gmvarkit.pdf
Vignettes: Introduction to gmvarkit
Package source: gmvarkit_1.4.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: gmvarkit_1.4.1.tgz, r-oldrel: gmvarkit_1.4.1.tgz
Old sources: gmvarkit archive


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