g('default') % Set the random number generator to the default seed st order autoregressive model (AR(1) can be defined in the following way. Y, = Py- + u. 1= 1,2.T. re y, denotes the value of y at time 1. p is a parameter and u, is a random variable that has a dard normal distribution. When p= 1, the model is called the random walk model. Assume yo = 0 (when t=0), and T=200. Use a for loop to generate 200 observations according this mode np=1 and p= 0.7. Plot your resulting observations in both cases. Your code snippet should ger figure given below. Recall that the normrnd function can be used to generate random numbers fro dard normal distribution Solution Random walk versus AR(1) 20 p0.7 15 10 20 40 60 80 100 120 140 160 180 200 ||

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Problem 4
Throughout this problem, consider the following setting:
rng('default') % Set the random number generator to the default seed
A first order autoregressive model (AR(1)) can be defined in the following way.
y= Py.- + u. 1= 1,2.T.
where y, denotes the value of y at time r, p is a parameter and u, is a random variable that has a
standard normal distribution. When p= 1, the model is called the random walk model. Assume
that y, = 0 (when t=), and T=200. Use a for loop to generate 200 observations according this model
when p=1 and p= 0.7. Plot your resulting observations in both cases. Your code snippet should generate
the figure given below. Recall that the normrnd function can be used to generate random numbers from the
standard normal distribution
* Solution
2
Random walk versus AR(1)
p0.7
15
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Transcribed Image Text:Problem 4 Throughout this problem, consider the following setting: rng('default') % Set the random number generator to the default seed A first order autoregressive model (AR(1)) can be defined in the following way. y= Py.- + u. 1= 1,2.T. where y, denotes the value of y at time r, p is a parameter and u, is a random variable that has a standard normal distribution. When p= 1, the model is called the random walk model. Assume that y, = 0 (when t=), and T=200. Use a for loop to generate 200 observations according this model when p=1 and p= 0.7. Plot your resulting observations in both cases. Your code snippet should generate the figure given below. Recall that the normrnd function can be used to generate random numbers from the standard normal distribution * Solution 2 Random walk versus AR(1) p0.7 15 10 20 40 60 80 100 120 140 160 180 200
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