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The random variables X1,..., Xn are independent and identically distributed with probability function PX (1 – Px)'-, x = 0, 1, 0, while the random variables Y1,.,Yn are independent and identically distributed with proba- Sx (2) = { P* (1 – px)"*, 0,1, otherwise, bility function )p% (1 – py)*-", y = 0, 1, 2, 0, where px and py are betwecn 0 and 1. Show that the maximum likelihood estimators (MLES) 2-y fy (y) = otherwise,

The random variables X1,..., Xn are independent and identically distributed with probability function PX (1 – Px)'-, x = 0, 1, 0, while the random variables Y1,.,Yn are independent and identically distributed with proba- Sx (2) = { P* (1 – px)"*, 0,1, otherwise, bility function )p% (1 – py)*-", y = 0, 1, 2, 0, where px and py are betwecn 0 and 1. Show that the maximum likelihood estimators (MLES) 2-y fy (y) = otherwise,

MATLAB: An Introduction with Applications
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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The random variables X1,... , Xn are independent and identically distributed with probability function Sx (=) = { P* (1 – px), x = 0, 1, 0, 1-r fx( otherwise, while the random variables Y,...,Yn are independent and identically distributed with proba- bility function Į )pš (1 – py)*-", 2-y y = 0, 1, 2, otherwise, fy (y) : 0, where Px and py are between 0 and 1. Show that the maximum likelihood estimators (MLES) of px and py are E Xi, Y;. 2n i=1 i=1
Transcribed Image Text:The random variables X1,... , Xn are independent and identically distributed with probability function Sx (=) = { P* (1 – px), x = 0, 1, 0, 1-r fx( otherwise, while the random variables Y,...,Yn are independent and identically distributed with proba- bility function Į )pš (1 – py)*-", 2-y y = 0, 1, 2, otherwise, fy (y) : 0, where Px and py are between 0 and 1. Show that the maximum likelihood estimators (MLES) of px and py are E Xi, Y;. 2n i=1 i=1
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