For each of the following regression models, indicate whether it is a general linear regres- sion model. If it is not, state whether it can be expressed in the form of (6.7) by a suitable transformation: a. Y; = ßo + ß₁X¿¡1 + ß2 log10 Xi2 + ß³X²₁ + ɛi b. Y; = ɛ; exp(ßo + ß₁ס1 + ß₂X²/2) c. Y; = log10(81X;1) + B2Xi2 + εi d. Y;=ẞo exp(ẞ₁X¡1) + εi e. Y; = [1+exp(ßo + B₁X₁₁ + ε¡)]¯¯¹
For each of the following regression models, indicate whether it is a general linear regres- sion model. If it is not, state whether it can be expressed in the form of (6.7) by a suitable transformation: a. Y; = ßo + ß₁X¿¡1 + ß2 log10 Xi2 + ß³X²₁ + ɛi b. Y; = ɛ; exp(ßo + ß₁ס1 + ß₂X²/2) c. Y; = log10(81X;1) + B2Xi2 + εi d. Y;=ẞo exp(ẞ₁X¡1) + εi e. Y; = [1+exp(ßo + B₁X₁₁ + ε¡)]¯¯¹
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
I just want the justification(calculation) of the answer below.
No AI solutions please
Answers: (a)-Yes, (b)-No, (c)-Yes, (d)-No, (e)-No
(6.7) form: Yi= β0+β1Xi1+β2Xi2+.....+βp-1Xi,p-1+εi
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