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Assume we want to estimate the parameters of a Bernoulli distribution p(x; 0) = 0² (1 - 0)¹-² using maximum likelihood estimation with the Bayesian approach. We are given univariate binary data [₁, 2,...,n] and the prior distribution has the form of p(0) = 0.40310 (1-0). Find the estimated parameter 0. Show all of your calculations.

Assume we want to estimate the parameters of a Bernoulli distribution p(x; 0) = 0² (1 - 0)¹-² using maximum likelihood estimation with the Bayesian approach. We are given univariate binary data [₁, 2,...,n] and the prior distribution has the form of p(0) = 0.40310 (1-0). Find the estimated parameter 0. Show all of your calculations.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Assume we want to estimate the parameters of a Bernoulli distribution p(x; 0) = 0² (1 - 0)¹-² using maximum likelihood estimation with the Bayesian approach. We are given univariate binary data [₁, 2,...,n] and the prior distribution has the form of p(0) = 0.40310 (1-0). Find the estimated parameter 0. Show all of your calculations.
Transcribed Image Text:Assume we want to estimate the parameters of a Bernoulli distribution p(x; 0) = 0² (1 - 0)¹-² using maximum likelihood estimation with the Bayesian approach. We are given univariate binary data [₁, 2,...,n] and the prior distribution has the form of p(0) = 0.40310 (1-0). Find the estimated parameter 0. Show all of your calculations.
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