✦ LIBER ✦

On Selecting a Power Transformation in Time-Series Analysis

✍ Scribed by Cathy W. S. Chen; Jack C. Lee

Publisher: John Wiley and Sons
Year: 1997
Tongue: English
Weight: 214 KB
Volume: 16
Category: Article
ISSN: 0277-6693
DOI: 10.1002/(sici)1099-131x(199709)16:5<343::aid-for665>3.0.co;2-j

No coin nor oath required. For personal study only.

✦ Synopsis

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. # 1997

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