Let Y 1 , Y 2 , , Y n be a random sample of size n from the pdf f Y (y ) 1 (r 1) r y r1ey , y 0 (a) Show that 1 r Y is an unbiased estimator for (b) Show that 1 r Y is a minimum variance estimator for ...

a Y is a gamma random variable with ...

Let Y 1 , Y 2 , . . . , Y n be a random sample

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Let Y₁, Y₂, . . . , Y_n be a random sample of size n from the pdf

f_Y(y; θ) = 1 (r −1)!θr y^{r−1e−y/θ}, y > 0

(a) Show that ˆθ = 1/r Y̅ is an unbiased estimator for θ.

(b) Show that ˆθ = 1/r Y̅ is a minimum-variance estimator for θ.

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Introduction To Mathematical Statistics And Its Applications

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Authors: Richard J. Larsen, Morris L. Marx

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Question Posted: Dec 20, 2015 03:34 AM

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Let Y 1 , Y 2 , . . . , Y n be a random sample

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