Consider the following parameterizations of the AR(1) process with nonzero mean: Suppose we want to estimate Model 1 Yµ = (Yt-1 - μ) + et - Model 2 Y Y₁-1+00+ et. = and μ (in Model 1) or o and 00 (in Model 2) via conditional least squares estimation on Y₁. Show that with Model 1 we need to solve nonlinear equations to obtain the estimates, while with Model 2 we only need to solve linear equations.
Consider the following parameterizations of the AR(1) process with nonzero mean: Suppose we want to estimate Model 1 Yµ = (Yt-1 - μ) + et - Model 2 Y Y₁-1+00+ et. = and μ (in Model 1) or o and 00 (in Model 2) via conditional least squares estimation on Y₁. Show that with Model 1 we need to solve nonlinear equations to obtain the estimates, while with Model 2 we only need to solve linear equations.
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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