Author: Panagiotis
19
Apr
In
[1, p. 61 exercise 3.6] we are asked to assume that the variance is to be estimated as well as the mean for the conditions of
[1, p. 60 exercise 3.4] (see also
[2, solution of exercise 3.4]) . We are asked to prove for the vector parameter
, that the Fisher information matrix is
Furthermore we are asked to find the CR bound and to determine if the sample mean
is efficient.
If additionaly the variance is to be estimated as
then we are asked to determine if this estimator is unbiased and efficient. Hint: We are instructed to use the result that
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Author: Panagiotis
11
Jan
In
[1, p. 61 exercise 3.5] we are asked to show that for the conditions of Problem
[1, p. 60, exercise 3.4] the CR bound is
and further to give a statement about the efficiency of the sample mean estimator.
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Author: Panagiotis
28
Dez
In
[1, p. 60 exercise 3.4] we are asked to prove that the estimate
is an unbiased estimator, given
are independent and identically distributed according to a
distribution. Furthermore we are asked to also find the variance of the estimator.
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In
[1, p. 60 exercise 3.3] we are asked to prove that the complex multivariate Gaussian PDF reduces to the complex univariate Gaussian PDF if N=1.
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In
[1, p. 60 exercise 3.2] we are asked to proof by using the method of characteristic functions that the sum of squares of N independent and identically distributed N(0,1) random variables has a
distribution.
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