DOI Number : 10.5614/itbj.sci.2012.44.3.2
Hits : 4

A Note on Prediction with Misspecified Model

Khreshna Syuhada,

Statistics Research Division,
Institut Teknologi Bandung
Jalan Ganesa 10 Bandung 40132 Indonesia

Abstract. Suppose that a time series model is fitted. It is likely that the fitted model is not the true model. In other words, the model has been misspecified. In this paper, we consider the prediction interval problem in the case of a misspecified first-order autoregressive or AR(1) model. We have calculated the coverage probability of an upper one-step-ahead prediction interval for both properly specified and misspecified models through Monte Carlo simulation. It was found that dealing with prediction interval for misspecified model is complicated: the distribution of a future observation conditional on the last observation and the parameter estimator is not identical to the distribution of this future observation conditional on the last observation alone.

Keywords: autoregressive; coverage probability; model misspecification; time series prediction.

Download Article
Bahasa Indonesia | English


Begin on 10 October 2014 this website is no longer activated for article process in Journal of Mathematical and Fundamental Sciences, Journal of Engineering and Technological Sciences, Journal of ICT Research and Applications and Journal of Visual Art and Design. The next process will be proceeded under new website at

For detail information please contact us to:

       ITB Journal Visitor Number #9593913       
       Jl. Tamansari 64, Bandung 40116, Indonesia Visitor IP Address #       
       Tel : +62-22-250 1759 ext. 121 2011 Institut Teknologi Bandung       
       Fax : +62-22-250 4010, +62-22-251 1215 XHTML + CSS + RSS       
       E-mail : or Developed by AVE