Browsing by Author "Chen, CWS"

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Bayesian estimation for time-series regressions improved with exact likelihoods
(2004-10-01)
Chen, CWS
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Lee, JC
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Lee, HY
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Niu, WF
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統計學研究所
We propose an estimation procedure for time-series regression models under the Bayesian inference framework. With the exact method of Wise [Wise, J. (1955). The autocorrelation function and spectral density function. Biometrika, 42, 151-159], an exact likelihood function can be obtained instead of the likelihood conditional on initial observations. The constraints on the parameter space arising from the stationarity conditions are handled by a reparametrization, which was not taken into consideration by Chib [Chib, S. (1993). Bayes regression with autoregressive errors: A Gibbs sampling approach. J. Econometrics, 58, 275-294] or Chib and Greenberg [Chib, S. and Greenberg, E. (1994). Bayes inference in regression model with ARMA(p, q) errors. J. Econometrics, 64, 183-206]. Simulation studies show that our method leads to better inferential results than their results.
On selecting a power transformation in time-series analysis
(1997-09-01)
Chen, CWS
;
Lee, JC
;
交大名義發表
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National Chiao Tung University
The primary aim of this paper is to select an appropriate power transformation when we use ARMA models for a given time series. We propose a Bayesian procedure for estimating the power transformation as well as other parameters in time series models. The posterior distributions of interest are obtained utilizing the Gibbs sampler, a Markov Chain Monte Carlo (MCMC) method. The proposed methodology is illustrated with two real data sets. The performance of the proposed procedure is compared with other competing procedures. (C) 1997 John Wiley & Sons, Ltd.