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

Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR) and Student's t Mixture Autoregressive (StMAR) models, quantile residual tests, graphical diagnostics, forecast and simulate from GMAR and StMAR processes. Also general linear constraints and restricting autoregressive parameters to be the same for all regimes are supported. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>, Leena Kalliovirta (2012) <doi:10.1111/j.1368-423X.2011.00364.x>.

Version: 1.0.1
Depends: R (≥ 3.3.2)
Imports: Brobdingnag (≥ 1.2-4), parallel, stats (≥ 3.3.2)
Suggests: gsl (≥ 1.9-10.3), pbapply (≥ 1.3-2), testthat, knitr, rmarkdown
Published: 2017-08-29
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen at helsinki.fi>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: uGMAR results

Downloads:

Reference manual: uGMAR.pdf
Vignettes: Introduction to uGMAR
Package source: uGMAR_1.0.1.tar.gz
Windows binaries: r-devel: uGMAR_1.0.1.zip, r-release: uGMAR_1.0.1.zip, r-oldrel: uGMAR_1.0.1.zip
OS X El Capitan binaries: r-release: uGMAR_1.0.1.tgz
OS X Mavericks binaries: r-oldrel: uGMAR_1.0.1.tgz
Old sources: uGMAR archive

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