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Consider the time series data set of 200 observations modelled as an AR(2) process x₁ = 0.9 x₁-₁-0.2 x₁-2 +Z₁, where Z-WN 0,0² . a) Write the process x, in backshift operator. b) Use Yule-Walker equations or otherwise to find the autocorrelation functions (ACFs) for x,. c) Calculate: (i) Φ11 · (ii) 22. (iii) Standard error for 33 33.

Consider the time series data set of 200 observations modelled as an AR(2) process x₁ = 0.9 x₁-₁-0.2 x₁-2 +Z₁, where Z-WN 0,0² . a) Write the process x, in backshift operator. b) Use Yule-Walker equations or otherwise to find the autocorrelation functions (ACFs) for x,. c) Calculate: (i) Φ11 · (ii) 22. (iii) Standard error for 33 33.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Consider the time series data set of 200 observations modelled as an AR(2) process x₁ = 0.9 x₁-₁-0.2 X₁-2 +Z₁, 1-1 where z, ~WN 0,0². a) Write the process x, in backshift operator. b) Use Yule-Walker equations or otherwise to find the autocorrelation functions (ACFs) for x, . c) Calculate: (i) Φη . (ii) Þ22. (iii) Standard error for $33.
Transcribed Image Text:Consider the time series data set of 200 observations modelled as an AR(2) process x₁ = 0.9 x₁-₁-0.2 X₁-2 +Z₁, 1-1 where z, ~WN 0,0². a) Write the process x, in backshift operator. b) Use Yule-Walker equations or otherwise to find the autocorrelation functions (ACFs) for x, . c) Calculate: (i) Φη . (ii) Þ22. (iii) Standard error for $33.
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