By Daniel Peña; George C Tiao; Ruey S Tsay
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Additional info for A course in time series analysis
1993). Elements of Multivariate Time-Series Analysis. Springer-Verlag, New York. Reinsel, G. C. and Velu, R. P. (1998). Multivariate Reduced Rank Regression. Springer-Verlag, New York. Ripley B. D. (1996). Pattern Recognition and Neural Networks. Cambridge Univ. Press, Cambridge, UK. Shumway, R. H. (1988). Applied Statistical Time Series Analysis. Prentice-Hall, Englewood Cliffs, NJ. Shumway, R. H. and Stoffer, D. A. (2000). Time Series Analysis and its Applications. SpringerVerlag, New York. Tiao, G.
W. S. (1990). Time Series Analysis. Addison-Wesley, Reading, MA. West, M. and Harrison, J. (1997). Bayesian Forecasting and Dynamic Models, 2nd ed. SpringerVerlag, New York. A Course in Time Series Analysis Edited by Daniel Рейа, George С Tiao and Ruey S. Tsay Copyright © 2001 John Wiley & Sons, Inc. PART I Basic Concepts in Univariate Time Series A Course in Time Series Analysis Edited by Daniel Рейа, George С Tiao and Ruey S. Tsay Copyright © 2001 John Wiley & Sons, Inc. C H A P T E R 2 Univariate Time Series: Autocorrelation, Linear Prediction, Spectrum, and State-Space Model G.
The scaling factor in the definition is chosen so that the area under the graph of / ( / ) is the mean square value of the series: J/=o η frf Usually the series is mean corrected before calculating the periodogram, so this becomes the sample variance. The periodogram then describes the distribution or analysis of the sample variance of the series over the frequency range. It is also common practice to scale the periodogram, dividing by the series variance so that the total area is unity. We shall choose a frequency grid with divisions of approximate width 1 /4n so that the periodogram appears continuous for most of our examples.
A course in time series analysis by Daniel Peña; George C Tiao; Ruey S Tsay