Explanation Calculation: The joint likelihood function of θ is obtained as follows: L ( θ ) = L ( Y 1 , Y 2 , ... , Y n | θ ) = ∏ i = 1 n ( θ + 1 ) Y i θ = ( θ + 1 ) n ∏ i = 1 n Y i θ The log likelihood function is obtained as follows: l ( θ ) = log ( ( θ + 1 ) n ∏ i = 1 n Y i θ ) = n log ( θ + 1 ) + θ ∑ i = 1 n log Y i Obtain the first order derivation of the log likelihood function with respect to θ and equate it with 0

Mathematical Statistics with Applications

7th Edition

ISBN: 9780495110811

Author: Dennis Wackerly, William Mendenhall, Richard L. Scheaffer

Publisher: Cengage Learning

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Question

Chapter 9.7, Problem 88E

To determine

Find the MLE of θ and compare the MLE of θ with the method of moment estimator of θ in Exercise 9.69.

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Chapter 9.7, Problem 87E

Chapter 9.7, Problem 89E

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Chapter 9 Solutions

Mathematical Statistics with Applications

Ch. 9.2 - Prob. 1E Ch. 9.2 - Let Y1, Y2,, Yn denote a random sample from a...Ch. 9.2 - Let Y1, Y2, , Yn denote a random sample from the...Ch. 9.2 - Let Y1, Y2, , Yn denote a random sample of size n...Ch. 9.2 - Suppose that Y1, Y2, , Yn is a random sample from...Ch. 9.2 - Prob. 6E Ch. 9.2 - Prob. 7E Ch. 9.2 - Let Y1, Y2, , Yn denote a random sample from a...Ch. 9.3 - Applet Exercise How was Figure 9.1 obtained?...Ch. 9.3 - Applet Exercise Refer to Exercise 9.9. Scroll down...

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