Let X₁, X2, X3,..., Xn denote a random sample of size n from the population distributed with the following probability density function: e) f) g) where k> 0 is a constant. f(x; λ) = 2-kxk-1e (k-1)! 0, if x > 0 elsewhere Justify whether or not  is a uniform minimum variance unbiased estimator of λ. Check whether or not the MLE of λ is a consistent. Suggest with a Fisher's factorization theorem, the sufficient estimator of 1.
Let X₁, X2, X3,..., Xn denote a random sample of size n from the population distributed with the following probability density function: e) f) g) where k> 0 is a constant. f(x; λ) = 2-kxk-1e (k-1)! 0, if x > 0 elsewhere Justify whether or not  is a uniform minimum variance unbiased estimator of λ. Check whether or not the MLE of λ is a consistent. Suggest with a Fisher's factorization theorem, the sufficient estimator of 1.
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter13: Probability And Calculus
Section13.CR: Chapter 13 Review
Problem 7CR
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![Let X₁, X2, X3,..., Xn denote a random sample of size n from the population distributed with the
following probability density function:
I
e)
f)
g)
where k> 0 is a constant.
f(x; 2) =
2-kxk-1e
(k-1)!
if x > 0
elsewhere
"
Justify whether or not  is a uniform minimum variance unbiased estimator of 1.
Check whether or not the MLE of λ is a consistent.
Suggest with a Fisher's factorization theorem, the sufficient estimator of 1.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc7f442cf-541d-4442-b6c8-0606c8499d0b%2Fd45b2426-8a81-4a2a-962c-825a290fe269%2Fb9zpasn_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Let X₁, X2, X3,..., Xn denote a random sample of size n from the population distributed with the
following probability density function:
I
e)
f)
g)
where k> 0 is a constant.
f(x; 2) =
2-kxk-1e
(k-1)!
if x > 0
elsewhere
"
Justify whether or not  is a uniform minimum variance unbiased estimator of 1.
Check whether or not the MLE of λ is a consistent.
Suggest with a Fisher's factorization theorem, the sufficient estimator of 1.
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