34. The mean squared error of an estimator Ô is MSE(Ô) = E(ô – ĝ)². If Ô is unbiased, then MSE(Ô) = V(Ô),but in general MSE(Ô) = V(Ô) + (bias)². Consider theestimator ²=KS2, where S² = sample variance. Whatvalue of K minimizes the mean squared error of this estima-tor when the population distribution is normal? [Hint: It canbe shown thatE[(S²)²] = (n + 1)σơ³/(n − 1)In general, it is difficult to find Ô to minimize MSE(Ô),which is why we look only at unbiased estimators andminimize V().]

Step 1: Given the estimator 𝜎2 = 𝐾𝑆2, we need to minimize the MSE of this estimator. Step 2: The…

Answered: 34. The mean squared error of an…

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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