Package: MMLR
Type: Package
Title: Fitting Markov-Modulated Linear Regression Models
Version: 0.2.0
Authors@R: c(
    person("Nadezda", "Spiridovska", email = "Spiridovska.N@tsi.lv", role = c("aut", "cre")),
    person("Diana", "Santalova", role = "ctb"))
Maintainer: Nadezda Spiridovska <Spiridovska.N@tsi.lv>
Description: 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. Markov-switching regression models
        have the same idea of varying the regression parameters
        randomly in accordance with external environment. The
        difference is that for Markov-modulated linear regression model
        the external environment is described as a continuous-time
        homogeneous irreducible Markov chain with known parameters
        while switching models consider Markov chain as unobserved and
        estimation procedure involves estimation of transition matrix.
        These models have significant differences in terms of the
        analytical approach. Also, package provides 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.
License: GPL (>= 2)
Encoding: UTF-8
Imports: stats, pracma
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2026-10-12 23:13:55 UTC; root
Author: Nadezda Spiridovska [aut, cre], Diana Santalova [ctb]
Repository: https://cranhaven.r-universe.dev
Date/Publication: 2026-10-12 09:02:00 UTC
RemoteUrl: https://github.com/cranhaven/cranhaven.r-universe.dev
RemoteRef: package/MMLR
RemoteSha: 3591335b37345db3dc19434dff50f69e73754f26
RemoteSubdir: MMLR