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BMTAR  

Bayesian Approach for MTAR Models with Missing Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BMTAR", "0.1.1")



Attach the package and use:
library("BMTAR")
Maintained by
Andrey Duvan Rincon Torres
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-06-09
Latest Update: 2021-01-19
Description:
Implements parameter estimation using a Bayesian approach for Multivariate Threshold Autoregressive (MTAR) models with missing data using Markov Chain Monte Carlo methods. Performs the simulation of MTAR processes (mtarsim()), estimation of matrix parameters and the threshold values (mtarns()), identification of the autoregressive orders using Bayesian variable selection (mtarstr()), identification of the number of regimes using Metropolised Carlin and Chib (mtarnumreg()) and estimate missing data, coefficients and covariance matrices conditional on the autoregressive orders, the threshold values and the number of regimes (mtarmissing()). Calderon and Nieto (2017) .
How to cite:
Andrey Duvan Rincon Torres (2020). BMTAR: Bayesian Approach for MTAR Models with Missing Data. R package version 0.1.1, https://cran.r-project.org/web/packages/BMTAR. Accessed 31 Jan. 2025.
Previous versions and publish date:
0.1.0 (2020-06-09 16:00)
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