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{X₁, X2, ...,Xn} be independent and identically distributed random variables with common pdf f(x) depending on two parameters a and b, a, b>0, where the variance is ab². It is known the following estimated value â³6³-320, where â and are the maximum likelihood estimates of a and b, respectively, and the estimated information matrix of (â, ô) is (1000 15 200). The estimated variance of the maximum likelihood estimator of the variance is equal to k, using the delta method. Find â and (in terms of k).

{X₁, X2, ...,Xn} be independent and identically distributed random variables with common pdf f(x) depending on two parameters a and b, a, b>0, where the variance is ab². It is known the following estimated value â³6³-320, where â and are the maximum likelihood estimates of a and b, respectively, and the estimated information matrix of (â, ô) is (1000 15 200). The estimated variance of the maximum likelihood estimator of the variance is equal to k, using the delta method. Find â and (in terms of k).

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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{X1,X2, ... ,Xn} be independent and identically distributed random variables with common pdf f (x) depending on two parameters a and b, a , b >0, where the variance is ab?. It is known the following estimated value â³ · 63=320, where â and b are the maximum likelihood estimates of a and b, respectively, and the estimated information matrix of (â, b) is (100 20 ). 15 200 The estimated variance of the maximum likelihood estimator of the variance is equal to k, using the delta method. Find â and b (in terms of k).
Transcribed Image Text:{X1,X2, ... ,Xn} be independent and identically distributed random variables with common pdf f (x) depending on two parameters a and b, a , b >0, where the variance is ab?. It is known the following estimated value â³ · 63=320, where â and b are the maximum likelihood estimates of a and b, respectively, and the estimated information matrix of (â, b) is (100 20 ). 15 200 The estimated variance of the maximum likelihood estimator of the variance is equal to k, using the delta method. Find â and b (in terms of k).
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