uppose X1, . . . , Xn are i.i.d. from a continuous distribution with p.d.f. fθ(x) = 1/θ if 0 ≤ x ≤ θ, where θ > 0 is an unknown parameter. (a) Find E(X1) ALREADY ANSWERED (b) Find the MME for θ. (c) Compute the variance of your MME from part (a).
uppose X1, . . . , Xn are i.i.d. from a continuous distribution with p.d.f. fθ(x) = 1/θ if 0 ≤ x ≤ θ, where θ > 0 is an unknown parameter. (a) Find E(X1) ALREADY ANSWERED (b) Find the MME for θ. (c) Compute the variance of your MME from part (a).
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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Suppose X1, . . . , Xn are i.i.d. from a continuous distribution with
fθ(x) = 1/θ if 0 ≤ x ≤ θ,
where θ > 0 is an unknown parameter.
(a) Find E(X1) ALREADY ANSWERED
(b) Find the MME for θ.
(c) Compute the variance of your MME from part (a).
I have asked this question multiple times and this last time it asked for clarification of whether it was MME (Methods of Moments Estimator) or MLE (Maximum Likelyhood Estimator). It calls for MME not MLE.
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