Residual Types in Time Series and Their Applications
Abstract
Residual types in time series has not been investigated throughly in literature. This study aims to provide practical applications of residual types. In this study, firstly, basic information about different types of residuals was given and some features of the residuals were investigated with numerical applications. Then a simulation study was conducted to show differences in decisions when different residual types were considered in diagnostic checking.
Keywords
References
- Ansley, C.F., Newbold, P., On the finite sample distribution of residual autocorrelations in autoregressive moving average models. Biometrika, 66:547-553 (1979).
- Akdi, Y., , Time Series Analysis (Unit Roots and Cointegration), Bıçaklar Bookstore, Ankara, 1-18 (2003).
- Arranz, M.A., Portmanteau Test Statistics in Time Series: Time-Oriented Language, 25-32 (2005) .
- Battaglia, F., “Approximate power of portmanteau tests for time series”, Statistics and Probability Letters, 9: 341 (1990).
- Box, G.E.P., Jenkins, G.M and Reinsel, G.C., Time Series analysis: Forecasting and a Control , Prentice Hall: New Jersey, 7-88, 224-307 (1994).
- Brockwell, P.J., Davis, R.A., Introduction to Time Series and Forecasting. Sec ond ed. Springer, NewYork (2002).
- Davies, N., Triggs, C. M. And :Newbold, P., “Significance levels of the Box-Pierce “Portmanteau statistic in finite samples”, Biometrika, 64: 517-522 (1977).
- Kasap, R., An analysis of the Istanbul Stock Exchange (ISE) national-100 index: a statistical approach. ISE Review, 6:27-33 (1998).
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Publication Date
April 16, 2012
Submission Date
November 27, 2011
Acceptance Date
-
Published in Issue
Year 2012 Volume: 25 Number: 2