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Given that (.vn, } be a realization of a random sample (Y1, Y,.., Y} on Y Select the statement in the folowing which is true Vaty d O HY-Poimon(6), then the maximum likelihood estimator (MLE) of 0 is EY and it is efficient since variance achieves Rao-Cramer lower bound O HY N(p, a"), both a and o are unknown, then ,Yis sufficient for a O HY N(p, o"), then is the maximum likelihood estimator (MLE) of a. O HY-1,p), then U- Y, is a minimum variance unbiased estimator (MVUE) for p

Given that (.vn, } be a realization of a random sample (Y1, Y,.., Y} on Y Select the statement in the folowing which is true Vaty d O HY-Poimon(6), then the maximum likelihood estimator (MLE) of 0 is EY and it is efficient since variance achieves Rao-Cramer lower bound O HY N(p, a"), both a and o are unknown, then ,Yis sufficient for a O HY N(p, o"), then is the maximum likelihood estimator (MLE) of a. O HY-1,p), then U- Y, is a minimum variance unbiased estimator (MVUE) for p

A First Course in Probability (10th Edition)
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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Given that (,,. } be a realiration of a random sample {Y, Y,..., Y} on Y Select the staterment in the foliowing which is true Valy ed O HY-Poison(6), then the maximum likelihood estimator (MLE) of 0 is Y, and it is efficient since variance achieves Rao-Cramer lower bound O HY- N(n,o), both a and o are unknown, then Y is sufficient for o² O HY N(n, o"), then is the maximum likelihood estimator (MLE) of . O #Yb(1,p), then U Y, is a minimum variance unbiased estimator (MVUE) for p.
Transcribed Image Text:Given that (,,. } be a realiration of a random sample {Y, Y,..., Y} on Y Select the staterment in the foliowing which is true Valy ed O HY-Poison(6), then the maximum likelihood estimator (MLE) of 0 is Y, and it is efficient since variance achieves Rao-Cramer lower bound O HY- N(n,o), both a and o are unknown, then Y is sufficient for o² O HY N(n, o"), then is the maximum likelihood estimator (MLE) of . O #Yb(1,p), then U Y, is a minimum variance unbiased estimator (MVUE) for p.
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