CRAN/E | BMTAR

BMTAR

Bayesian Approach for MTAR Models with Missing Data

Installation

About

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) doi:10.1080/03610926.2014.990758.

Key Metrics

Version 0.1.1
R ≥ 3.6.0
Published 2021-01-19 1195 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks BMTAR results

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Maintainer

Maintainer

Andrey Duvan Rincon Torres

adrincont@unal.edu.co

Authors

Valeria Bejarano Salcedo
Sergio Alejandro Calderon Villanueva Andrey Duvan Rincon Torres

Material

README
NEWS
Reference manual
Package source

In Views

MissingData
TimeSeries

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

BMTAR archive

Depends

R ≥ 3.6.0

Imports

Brobdingnag
MASS
MCMCpack
expm
ks
mvtnorm
compiler
doParallel
parallel
ggplot2