uGMAR: Estimate Univariate Gaussian or Student's t Mixture Autoregressive Model

Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR), Student's t Mixture Autoregressive (StMAR), and Gaussian and Student's t Mixture Autoregressive (G-StMAR) models, quantile residual tests, graphical diagnostics, forecast and simulate from GMAR, StMAR and G-StMAR processes. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>, Mika Meitz, Daniel Preve, Pentti Saikkonen (2018) <arXiv:1805.04010>, Savi Virolainen (2020) <arXiv:2003.05221>.

Version: 3.2.6
Depends: R (≥ 3.4.0)
Imports: Brobdingnag (≥ 1.2-4), parallel, pbapply (≥ 1.3-2), stats (≥ 3.3.2)
Suggests: gsl (≥ 1.9-10.3), testthat, knitr, rmarkdown
Published: 2020-12-17
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: uGMAR results


Reference manual: uGMAR.pdf
Vignettes: Introduction to uGMAR
Package source: uGMAR_3.2.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: uGMAR_3.2.6.tgz, r-oldrel: uGMAR_3.2.6.tgz
Old sources: uGMAR archive


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