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Unformatted text preview: TIME-SERIES ANALYSIS: PASCAL PROGRAM This program demonstrates alternative ways of characterising a stationary stochastic process. On the one hand are the time-domain characterisations, which depend upon the autocorrelation and partial autocorrelation functions. These functions convey the same information in different forms. On the other hand is the frequency-domain characterisation, which is provided by the spec- tral density function. This conveys the same information as the autocorrelation functions. The program first asks the user to specify the parameters of a stationary autoregressive moving-average model. It proceeds to generate the corresponding autocorrelation functions and the spectral density function. The program also generates a pseudo random sequence from which the empirical autocorrelation functions can be calculated and compared to their theoretical counterparts. The Menu The TSERIES program displays the following menu: TIME-SERIES ANALYSIS 1. Get Page Parameters 2. Get Model Parameters 3. Get the Data and Plot it 4. SACF: Sample Autocorrelation Function 5. SPACF: Sample Partial Autocorrelation Function 6. TACF: Theoretical Autocorrelation Function 7. TPACF: Theoretical Partial Autocorrelation Function 8. Spectral Density Function 9. Periodogram 10. FOR EXIT The manner in which the program operates is largely self-explanatory. It poses questions that are typically answered by typing...
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This note was uploaded on 03/02/2012 for the course EC 3062 taught by Professor D.s.g.pollock during the Spring '12 term at Queen Mary, University of London.

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