Let X_1, X_2, ... , X_2 be i.i.d. from Normal(0, sigma^2), sigma > 0 (a) Find the maximum likelihood estimator (MLE) of sigma^2 (b) If T^2 is the MLE of sigma^2, find a constant K so that Expectation: E(K * T^2) = sigma^2 (c) Let T = sqrt(T^2), Find a constant C so that C*T is unbiased for sigma.

Let X_1, X_2, ... , X_2 be i.i.d. from Normal(0, sigma^2), sigma > 0 (a) Find the maximum likelihood estimator (MLE) of sigma^2 (b) If T^2 is the MLE of sigma^2, find a constant K so that Expectation: E(K * T^2) = sigma^2 (c) Let T = sqrt(T^2), Find a constant C so that C*T is unbiased for sigma.

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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Question

Let X_1, X_2, ... , X_2 be i.i.d. from Normal(0, sigma^2), sigma > 0

(a) Find the maximum likelihood estimator (MLE) of sigma^2

(b) If T^2 is the MLE of sigma^2, find a constant K so that Expectation: E(K * T^2) = sigma^2

please answer (b) and (c). the answer to a) is shown here.

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