標題: On selecting a power transformation in time-series analysis
作者: Chen, CWS
Lee, JC
交大名義發表
National Chiao Tung University
關鍵字: ARMA models;Forecasting;Gibbs sampler;MCMC method;power transformation
公開日期: 1-九月-1997
摘要: 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.
URI: http://hdl.handle.net/11536/14555
ISSN: 0277-6693
期刊: JOURNAL OF FORECASTING
Volume: 16
Issue: 5
起始頁: 343
結束頁: 354
顯示於類別:期刊論文


文件中的檔案:

  1. A1997YD78100005.pdf