Let Y₁, Y2, ..., Y₁ denote a random sample of size n from a population whose density is given by [αya-1/0⁰, 0≤ y ≤ 0, elsewhere, ro=lo = - where a > 0 is a known, fixed value, but is unknown. (This is the power family distribution introduced in Exercise 6.17.) Consider the estimator Ô = max(Y₁, Y₂, ..., Yn). a Show that Ô is a biased estimator for 0. b Find a multiple of ô that is an unbiased estimator of 0. C Derive MSE(Ô).

MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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Let Y₁, Y2, ..., Yn denote a random sample of size n from a population whose density is given by
aya-1/0⁰, 0≤ y ≤0,
elsewhere,
a
0,
where a > 0 is a known, fixed value, but ◊ is unknown. (This is the power family distribution
introduced in Exercise 6.17.) Consider the estimator ô = max(Y₁, Y2, . . ., Yn).
b
ƒ(y)
C
=
Show that is a biased estimator for 0.
Find a multiple of Ô that is an unbiased estimator of 0.
Derive MSE(Ô).
Transcribed Image Text:Let Y₁, Y2, ..., Yn denote a random sample of size n from a population whose density is given by aya-1/0⁰, 0≤ y ≤0, elsewhere, a 0, where a > 0 is a known, fixed value, but ◊ is unknown. (This is the power family distribution introduced in Exercise 6.17.) Consider the estimator ô = max(Y₁, Y2, . . ., Yn). b ƒ(y) C = Show that is a biased estimator for 0. Find a multiple of Ô that is an unbiased estimator of 0. Derive MSE(Ô).
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