uGMAR: Estimate Univariate Gaussian and Student's t Mixture Autoregressive Models

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 (2023) <doi:10.1080/03610926.2021.1916531>, Savi Virolainen (2022) <doi:10.1515/snde-2020-0060>.

Version: 3.4.5
Depends: R (≥ 3.4.0)
Imports: Brobdingnag (≥ 1.2-4), parallel, pbapply (≥ 1.3-2), stats (≥ 3.3.2), gsl (≥ 1.9-10.3)
Suggests: testthat, knitr, rmarkdown
Published: 2023-08-19
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: uGMAR results


Reference manual: uGMAR.pdf
Vignettes: uGMAR: A Family of Mixture Autoregressive Models in R


Package source: uGMAR_3.4.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): uGMAR_3.4.5.tgz, r-oldrel (arm64): uGMAR_3.4.5.tgz, r-release (x86_64): uGMAR_3.4.5.tgz, r-oldrel (x86_64): uGMAR_3.4.5.tgz
Old sources: uGMAR archive


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