Package: MMLR 0.2.0

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. 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.

Authors:Nadezda Spiridovska [aut, cre], Diana Santalova [ctb]

MMLR_0.2.0.tar.gz
MMLR_0.2.0.zip(r-4.5)MMLR_0.2.0.zip(r-4.4)MMLR_0.2.0.zip(r-4.3)
MMLR_0.2.0.tgz(r-4.5-any)MMLR_0.2.0.tgz(r-4.4-any)MMLR_0.2.0.tgz(r-4.3-any)
MMLR_0.2.0.tar.gz(r-4.5-noble)MMLR_0.2.0.tar.gz(r-4.4-noble)
MMLR_0.2.0.tgz(r-4.4-emscripten)MMLR_0.2.0.tgz(r-4.3-emscripten)
MMLR.pdf |MMLR.html
MMLR/json (API)

# Install 'MMLR' in R:
install.packages('MMLR', repos = c('https://nadezdaspiridovska.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 3 scripts 124 downloads 1 mentions 8 exports 1 dependencies

Last updated 5 years agofrom:01956115b9. Checks:3 OK, 6 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKApr 01 2025
R-4.5-winNOTEApr 01 2025
R-4.5-macNOTEApr 01 2025
R-4.5-linuxNOTEApr 01 2025
R-4.4-winNOTEApr 01 2025
R-4.4-macNOTEApr 01 2025
R-4.4-linuxNOTEApr 01 2025
R-4.3-winOKApr 01 2025
R-4.3-macOKApr 01 2025

Exports:Aver_soj_timeB_estrandomizeInitStaterandomizeTaurandomizeXVarYXregYsimulation

Dependencies:pracma