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A wrapper function for the estimation of regime switching autoregressive models, including multivariate case (MS-VAR) is included in the package.
![matlab polytool regress matlab polytool regress](https://i.stack.imgur.com/xDWvJ.jpg)
This means that you can choose which coefficients in the model, including distribution parameters, are switching states over time Estimation, by maximum likelihood, of any type of switching setup for the model.Support of any number of states and any number of explanatory variables.Support for univariate and multivariate models.Please be aware that the R version in no longer being maintained so it is actually an older version of the matlab package with only the basic features. It is public available in the R Metrics project and in R Code section of my website. I also wrote a R version of the package (fMarkovSwitching). You can modify the examples for you own dataset and custom model.
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They should work as is, without any modification. The easiest way to get started is to run the example scripts provided in the root folder. After that, all functions will be available to the user. In order to use the functions of MS_Regress, all you need to do is to tell matlab to look for the files in the m_Files folder (e.g. Matlab works by reading files in the search path. Instalationįirst, clone this repository or download it as a zip file (see download choice in right side button of the webpage). I switched to R back in 2015 and never looked back. A copy of this paper can be found in SSRN.īe aware that this Matlab code is no longer being maintained.
MATLAB POLYTOOL REGRESS PDF
This repository provides functions (and examples scripts) for the estimation, simulation and forecasting of a general Markov Regime Switching Regression in Matlab.īefore using the package, make sure you read the pdf file (About the MS_Regress_Package.pdf) in the downloaded zip file.