(following Larsen & Marx, exercise 5.6.5) Let ?1, ?2, …, ?? be the random sample of a positive random variable ? having the density function: ?? (?; ?) = 1 /41! ? 42 ? 41? − ? ? with one parameter ? ∈ ℝ +. Find an estimator for ? that is sufficient.Note : in the following image replace 5 with 41 and 6 with 42. (following Larsen & Marx, exercise 5.6.5)Let X1, X2,.., X, be the random sample of a positive random variable X having the density function:1fz(x; 0) = ;-xše5! 06with one parameter 0 € R*. Find an estimator for 0 that is sufficient.

By using Neyman Factorization sufficiency theorem.............

(following Larsen & Marx, exercise 5.6.5) Let X1, X2,.., X, be the random sample of a positive random variable X having the density function: 1 fx(x; 0) : 5! 06 with one parameter 0 € R*. Find an estimator for 0 that is sufficient.

(following Larsen & Marx, exercise 5.6.5) Let X1, X2,.., X, be the random sample of a positive random variable X having the density function: 1 fx(x; 0) : 5! 06 with one parameter 0 € R*. Find an estimator for 0 that is sufficient.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

(following Larsen & Marx, exercise 5.6.5) Let ?1, ?2, …, ?? be the random sample of a positive random variable ? having the density function: ?? (?; ?) = 1 /41! ? 42 ? 41? − ? ? with one parameter ? ∈ ℝ +. Find an estimator for ? that is sufficient.

Note : in the following image replace 5 with 41 and 6 with 42.

(following Larsen & Marx, exercise 5.6.5)
Let X1, X2,.., X, be the random sample of a positive random variable X having the density function:
1
fz(x; 0) = ;
-xše
5! 06
with one parameter 0 € R*. Find an estimator for 0 that is sufficient.

Expression, rule, or law that gives the relationship between an independent variable and dependent variable. Some important types of functions are injective function, surjective function, polynomial function, and inverse function.

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