MMLR: Fitting Markov-Modulated Linear Regression Models

A set of tools for fitting Markov-modulated linear regression, where responses Y(t) are time-additive, and model operates in the external environment, which is described as a continuous time Markov chain with finite state space. Model is proposed by Alexander Andronov (2012) <arXiv:1901.09600v1> and algorithm of parameters estimation is based on eigenvalues and eigenvectors decomposition. Also, package will provide a set of data simulation tools for Markov-modulated linear regression (for academical/research purposes). Research project No. 1.1.1.2/VIAA/1/16/075.

Version: 0.1.0
Imports: matlib
Published: 2019-02-03
Author: Nadezda Spiridovska [aut, cre], Diana Santalova [ctb]
Maintainer: Nadezda Spiridovska <Spiridovska.N at tsi.lv>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: MMLR results

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Reference manual: MMLR.pdf
Package source: MMLR_0.1.0.tar.gz
Windows binaries: r-devel: MMLR_0.1.0.zip, r-release: MMLR_0.1.0.zip, r-oldrel: MMLR_0.1.0.zip
OS X binaries: r-release: MMLR_0.1.0.tgz, r-oldrel: MMLR_0.1.0.tgz

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