1. Find the MLE of 0 based on a random sample X₁, X₂,..., Xn from each of the following p.d.f.'s. (a) where 0 < x < 1, 0 < 0, and 0 otherwise. (b) f(x|0) = 0x0-1 f(x0) = (0+1)x-0-2 where 1 < x, 0 < 0, and 0 otherwise. (c) where 0 < x, 0 <0, and 0 otherwise. f(z\0) = 0°xe-Đ

MATLAB: An Introduction with Applications
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1. Find the MLE of \( \theta \) based on a random sample \( X_1, X_2, ..., X_n \) from each of the following p.d.f.'s:

   (a)  \( f(x|\theta) = \theta x^{\theta-1} \)

   where \( 0 < x < 1, \ 0 < \theta, \) and 0 otherwise.

   (b)  \( f(x|\theta) = (\theta + 1) x^{-\theta-2} \)

   where \( 1 < x, \ 0 < \theta, \) and 0 otherwise.

   (c)  \( f(x|\theta) = \theta^2 x e^{-\theta x} \)

   where \( 0 < x, \ 0 < \theta, \) and 0 otherwise.

   (d)  \( f(x|\theta) = \theta (1 - \theta)^{x-1} \)

   for \( x = 1, 2, ..., \ 0 < \theta < 1, \) and 0 otherwise.

2. Find the asymptotic variance of the MLE in each part of question 1.
Transcribed Image Text:1. Find the MLE of \( \theta \) based on a random sample \( X_1, X_2, ..., X_n \) from each of the following p.d.f.'s: (a) \( f(x|\theta) = \theta x^{\theta-1} \) where \( 0 < x < 1, \ 0 < \theta, \) and 0 otherwise. (b) \( f(x|\theta) = (\theta + 1) x^{-\theta-2} \) where \( 1 < x, \ 0 < \theta, \) and 0 otherwise. (c) \( f(x|\theta) = \theta^2 x e^{-\theta x} \) where \( 0 < x, \ 0 < \theta, \) and 0 otherwise. (d) \( f(x|\theta) = \theta (1 - \theta)^{x-1} \) for \( x = 1, 2, ..., \ 0 < \theta < 1, \) and 0 otherwise. 2. Find the asymptotic variance of the MLE in each part of question 1.
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