Other packages > Find by keyword >

MMLR  

Fitting Markov-Modulated Linear Regression Models
View on CRAN: Click here


Download and install MMLR package within the R console
Install from CRAN:
install.packages("MMLR")

Install from Github:
library("remotes")
install_github("cran/MMLR")

Install by package version:
library("remotes")
install_version("MMLR", "0.2.0")



Attach the package and use:
library("MMLR")
Maintained by
Nadezda Spiridovska
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-02-03
Latest Update: 2020-01-09
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) 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.
How to cite:
Nadezda Spiridovska (2019). MMLR: Fitting Markov-Modulated Linear Regression Models. R package version 0.2.0, https://cran.r-project.org/web/packages/MMLR. Accessed 26 Jun. 2026.
Previous versions and publish date:
0.1.0 (2019-02-03 17:33)
Other packages that cited MMLR R package
View MMLR citation profile
Other R packages that MMLR depends, imports, suggests or enhances
Complete documentation for MMLR
Functions, R codes and Examples using the MMLR R package
Some associated functions: Aver_soj_time . B_est . VarY . Xreg . Ysimulation . randomizeInitState . randomizeTau . randomizeX . 
Some associated R codes: MMLR-package.R . MMLR.R .  Full MMLR package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

colormap  
Color Palettes using Colormaps Node Module
Allows to generate colors from palettes defined in the colormap module of 'Node.js'. (see ...
Download / Learn more Package Citations See dependency  
ggblanket  
Simplify 'ggplot2' Visualisation
Simplify 'ggplot2' visualisation with 'ggblanket' wrapper functions. ...
Download / Learn more Package Citations See dependency  
poptrend  
Estimate Smooth and Linear Trends from Population Count Survey Data
Functions to estimate and plot smooth or linear population trends, or population indices, from anim ...
Download / Learn more Package Citations See dependency  
PoisBinOrdNor  
Data Generation with Poisson, Binary, Ordinal and Normal Components
Generation of multiple count, binary, ordinal and normal variables simultaneously given the marginal ...
Download / Learn more Package Citations See dependency  
infotheo  
Information-Theoretic Measures
Implements various measures of information theory based on several entropy estimators. ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  

27,535

R Packages

236,180

Dependencies

73,223

Author Associations

27,536

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA