b. Suppose that et is zero mean white noise with var(et) = o. Consider the process: i. ii. iii. iv. Y₂ = 1+0.4Yt-1 + e - 0.3e-1 0.15e-2 Write the model using lag operator notation. Assess if the process is covariance stationary. Identify this model as an ARIMA (p, d, q) process; that is, specify p, d, and q. Find μ = E(Y₂).
b. Suppose that et is zero mean white noise with var(et) = o. Consider the process: i. ii. iii. iv. Y₂ = 1+0.4Yt-1 + e - 0.3e-1 0.15e-2 Write the model using lag operator notation. Assess if the process is covariance stationary. Identify this model as an ARIMA (p, d, q) process; that is, specify p, d, and q. Find μ = E(Y₂).
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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Transcribed Image Text:b. Suppose that e, is zero mean white noise with var(et) = o. Consider the process:
i.
ii.
iii.
iv.
Y₁ = 1+0.4Y-1 + et - 0.3e-1
0.15€t-2
Write the model using lag operator notation.
Assess if the process is covariance stationary.
Identify this model as an ARIMA (p, d, q) process; that is, specify p, d, and q.
Find μ = E(Y).
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