a. n Let X₁,..., X be a random sample from a uniform distribution on [0, 0]. Then the mle of is ô = Y = max(X;). Use the fact that Y≤y iff each X; ≤y to derive the cdf of Y. Then show that the pdf of Y = max(X) is nyn-1 Ꮎn 0 fy(y) = { 0≤ y ≤ 0 otherwise b. Use the result of part (a) to show that the mle is biased but that (n + 1)max(X;)/n is unbiased.
a. n Let X₁,..., X be a random sample from a uniform distribution on [0, 0]. Then the mle of is ô = Y = max(X;). Use the fact that Y≤y iff each X; ≤y to derive the cdf of Y. Then show that the pdf of Y = max(X) is nyn-1 Ꮎn 0 fy(y) = { 0≤ y ≤ 0 otherwise b. Use the result of part (a) to show that the mle is biased but that (n + 1)max(X;)/n is unbiased.
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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![a.
n
Let X₁,..., X be a random sample from a uniform
distribution on [0, 0]. Then the mle of 0 is
ô = Y = max(X;). Use the fact that Y≤y iff each
X; ≤y to derive the cdf of Y. Then show that the pdf
of Y = max(X) is
fx(v)
nyn-1
Ꮎn
0
=
ľ
0≤ y ≤ 0
otherwise
b. Use the result of part (a) to show that the mle is
biased but that (n + 1)max(X;)/n is unbiased.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fbf8ee92f-ba39-4be8-985d-aa9c69d8e21c%2Fe7b76614-f050-45e2-8a2f-d31890b0b5e0%2Fsi6vlso_processed.png&w=3840&q=75)
Transcribed Image Text:a.
n
Let X₁,..., X be a random sample from a uniform
distribution on [0, 0]. Then the mle of 0 is
ô = Y = max(X;). Use the fact that Y≤y iff each
X; ≤y to derive the cdf of Y. Then show that the pdf
of Y = max(X) is
fx(v)
nyn-1
Ꮎn
0
=
ľ
0≤ y ≤ 0
otherwise
b. Use the result of part (a) to show that the mle is
biased but that (n + 1)max(X;)/n is unbiased.
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