4. Consider the AR(3) model: y, = 0.216y,-3 + ,1e)-WN(0, 1). (a) Find the solutions (roots) of the autoregressive (characteristic) polynomial. Is this model weakly stationary? (b) If z, = (1 –- B)y,, where B denotes the backward shifts operator, which (ARIMA) model does z, follow? Is z, stationary? %3D (c) If y2019 = 0.6, y2020 = 0.5 and y2021 = 1, find the (mean-square optimal) forecasts of y2022 and y2023- (d) Compute the autocovariances y(0) and y(1) of (y,).
4. Consider the AR(3) model: y, = 0.216y,-3 + ,1e)-WN(0, 1). (a) Find the solutions (roots) of the autoregressive (characteristic) polynomial. Is this model weakly stationary? (b) If z, = (1 –- B)y,, where B denotes the backward shifts operator, which (ARIMA) model does z, follow? Is z, stationary? %3D (c) If y2019 = 0.6, y2020 = 0.5 and y2021 = 1, find the (mean-square optimal) forecasts of y2022 and y2023- (d) Compute the autocovariances y(0) and y(1) of (y,).
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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