Let x1, X2 ... Xn d n(0, 0). That is, o = q² in the usual notation and the likelihood function %%%%joint density of X1, X2, …- , Xn is as follows. L(0) = 0 > 0. exp (2x®)yn/2 Now the parameter space 2 = (0, 00). Obtain the Cramer-Rao lower bound, for unbiased estimators of e. The following "answers" have been proposed. (a) The C-R lower bound is e2(n – 1). (b) The C-R lower bound is 20²(n – 1). (c) The C-R lower bound is 202/n. (d) The C-R lower bound is o²m. (e) None of the above. The correct answer is (а) (b) (c) (d) (e) N/A (Select One)

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Let x1, X2, ... , Xn üd n(0, 0). That is, 0 = g² in the usual notation and the likelihood function %%%%joint density of
iid
X1, X2, .. , Xn is as follows.
n
1
L(0) =
exp
0 > 0.
(270)n/2
Now the parameter space N = (0, 0). Obtain the Cramer-Rao lower bound, for unbiased estimators of e.
The following`answers" have been proposed.
(a) The C-R lower bound is 0²1(n – 1).
(b) The C-R lower bound is 202/(n – 1).
(c) The C-R lower bound is 202/n.
(d) The C-R lower bound is 0²In.
(e) None of the above.
The correct answer is
(а)
(b)
(c)
(d)
(e)
N/A
(Select One)
Transcribed Image Text:Let x1, X2, ... , Xn üd n(0, 0). That is, 0 = g² in the usual notation and the likelihood function %%%%joint density of iid X1, X2, .. , Xn is as follows. n 1 L(0) = exp 0 > 0. (270)n/2 Now the parameter space N = (0, 0). Obtain the Cramer-Rao lower bound, for unbiased estimators of e. The following`answers" have been proposed. (a) The C-R lower bound is 0²1(n – 1). (b) The C-R lower bound is 202/(n – 1). (c) The C-R lower bound is 202/n. (d) The C-R lower bound is 0²In. (e) None of the above. The correct answer is (а) (b) (c) (d) (e) N/A (Select One)
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