Observation data {X_1,...,Xn} give the sample partial autocorrelation function values alpha(1)=0.9, alpha(2)=0.5, alpha(3)=-0.1, alpha(4)=0.2, alpha(5)=0.1. Based on these values, what is the appropriate order p of the autoregressive process AR(p) to model this dataset? A 2 B 3 C 4 D 5
Observation data {X_1,...,Xn} give the sample partial autocorrelation function values alpha(1)=0.9, alpha(2)=0.5, alpha(3)=-0.1, alpha(4)=0.2, alpha(5)=0.1. Based on these values, what is the appropriate order p of the autoregressive process AR(p) to model this dataset? A 2 B 3 C 4 D 5
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:Observation data {X_1,...,Xn} give the sample partial autocorrelation function values alpha(1)=0.9, alpha(2)=0.5,
alpha(3)=-0.1, alpha(4)=0.2, alpha(5)=0.1. Based on these values, what is the appropriate order p of the
autoregressive process AR(p) to model this dataset?
A 2
с 4
D
For process X_n=2X_{n-1}-X_{n=2}+Z_n, where Z_n is white noise, which statement is true?
A The process is stationary
В
After difference, the process is stationary
C
After the second difference, the process is stationary
D
None of the above
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