BAYSTAR: On Bayesian analysis of Threshold autoregressive model (BAYSTAR)

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The manuscript introduces the BAYSTAR package, which provides the functionality for Bayesian estimation in autoregressive threshold models.

Author
Cathy W. S. Chen, Edward M.H. Lin, F.C. Liu, and Richard Gerlach
Date of publication
2013-09-27 07:58:54
Maintainer
Edward M.H. Lin <m9281067@gmail.com>
License
GPL (>= 2)
Version
0.2-9

View on CRAN

Man pages

BAYSTAR
Threshold Autoregressive model: Bayesian approach
TAR.coeff
Estimate AR coefficients
TAR.lagd
Identification of lag order of threshold variable
TAR.lik
Log-likelihood function
TAR.sigma
To draw the variance of error distribution.
TAR.simu
Simulated data from TAR model
TAR.summary
Calculate summary statistics for all parameters
TAR.thres
To draw a threshold value.
unemployrate
U.S. monthly civilian unemployment rate

Files in this package

BAYSTAR
BAYSTAR/COPYING
BAYSTAR/NAMESPACE
BAYSTAR/CHANGELOG
BAYSTAR/data
BAYSTAR/data/unemployrate.rda
BAYSTAR/R
BAYSTAR/R/TAR.thres.R
BAYSTAR/R/TAR.sigma.R
BAYSTAR/R/TAR.summary.R
BAYSTAR/R/BAYSTAR.R
BAYSTAR/R/TAR.coeff.R
BAYSTAR/R/TAR.simu.R
BAYSTAR/R/TAR.lik.R
BAYSTAR/R/TAR.lagd.R
BAYSTAR/R/zzz.R
BAYSTAR/MD5
BAYSTAR/DESCRIPTION
BAYSTAR/man
BAYSTAR/man/BAYSTAR.Rd
BAYSTAR/man/unemployrate.Rd
BAYSTAR/man/TAR.simu.Rd
BAYSTAR/man/TAR.thres.Rd
BAYSTAR/man/TAR.summary.Rd
BAYSTAR/man/TAR.sigma.Rd
BAYSTAR/man/TAR.coeff.Rd
BAYSTAR/man/TAR.lagd.Rd
BAYSTAR/man/TAR.lik.Rd