Let {X1, X2, ... , Xn} be a random sample from the normal distribution n(µ, o²). A com used unbiased estimator for o? is the sample variance defined by n 1 S? : E(X; – X)². n - i=1 (a) Find the MSE (Mean squared error) of S². (b) Another commonly adopted definition of the sample variance is given by E(X; – X)² п — S². n –1 s2 SD - Find the MSE of SD² as an estimator of o? and compare it to S². Which one is better? (c) Suppose that we seek for an estimator that takes the form ô? constant. Find the value ofc such that ô² has the smallest MSE among all the estimators form of cS?. cS?, where c is some p-
Let {X1, X2, ... , Xn} be a random sample from the normal distribution n(µ, o²). A com used unbiased estimator for o? is the sample variance defined by n 1 S? : E(X; – X)². n - i=1 (a) Find the MSE (Mean squared error) of S². (b) Another commonly adopted definition of the sample variance is given by E(X; – X)² п — S². n –1 s2 SD - Find the MSE of SD² as an estimator of o? and compare it to S². Which one is better? (c) Suppose that we seek for an estimator that takes the form ô? constant. Find the value ofc such that ô² has the smallest MSE among all the estimators form of cS?. cS?, where c is some p-
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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Transcribed Image Text:Let {X1, X2,..., Xn} be a random sample from the normal distribution n(µ, o²). A commonly
used unbiased estimator for o? is the sample variance defined by
n
1
S?
E(X; - X)².
1
i=1
(a) Find the MSE (Mean squared error) of S².
(b) Another commonly adopted definition of the sample variance is given by
n
1
(X; – X)² =
п — 1
SD?
n2(X; -
i=1
Find the MSE of SD² as an estimator of o? and compare it to S². Which one is better?
cS², where c is some positive
(c) Suppose that we seek for an estimator that takes the form ô?
constant. Find the value of c such that ô² has the smallest MSE among all the estimators in the
form of cS?.
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