1. What is your guess on the value of p? 2. In Maximum Likelihood Estimation, we want to find a parameter p which maximizes all the observations in the dataset. If the dataset is a matrix A, where each row a1, a2,,am are individual observations, we want to maximize P(A) = P(a₁)P(a₂) P(am) because individ- ual experiments are independent. Maximizing this is equivalent to maximizing log P(A) = log P(a₁)+log P(a₂)+…+log P(am). Maximizing this quantity is equivalent to minimizing the -log P(A) = -log P(a₁) - log P(a₂)log P(am). 3. Here you need to find out P(ai) for yourself. 4. If you can do that properly, you will find an equation of the form: Now, define q = m mn -log P(A) mn Σi=121 mn log p Σ=1 yi mn log (1 - p) Then the equation becomes: -log P(A) -q logp (1-q) log (1 − p) mn Use Pinsker's Inequality or Calculus to show that, p = q. 5. What is the value of p for the above dataset given in the table? 6. If you toss 20 coins now, how many coins are most likely to yield a head?
1. What is your guess on the value of p? 2. In Maximum Likelihood Estimation, we want to find a parameter p which maximizes all the observations in the dataset. If the dataset is a matrix A, where each row a1, a2,,am are individual observations, we want to maximize P(A) = P(a₁)P(a₂) P(am) because individ- ual experiments are independent. Maximizing this is equivalent to maximizing log P(A) = log P(a₁)+log P(a₂)+…+log P(am). Maximizing this quantity is equivalent to minimizing the -log P(A) = -log P(a₁) - log P(a₂)log P(am). 3. Here you need to find out P(ai) for yourself. 4. If you can do that properly, you will find an equation of the form: Now, define q = m mn -log P(A) mn Σi=121 mn log p Σ=1 yi mn log (1 - p) Then the equation becomes: -log P(A) -q logp (1-q) log (1 − p) mn Use Pinsker's Inequality or Calculus to show that, p = q. 5. What is the value of p for the above dataset given in the table? 6. If you toss 20 coins now, how many coins are most likely to yield a head?
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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Please give a step-by-step solution to parts 4, 5, and 6.
This problem is on Maximum Likelihood Estimation.
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Step 1: Write the given information.
VIEWStep 2: Determine the guess for the p value and determine the maximum likelihood estimator.
VIEWStep 3: Determine the value of P(ai) using Binomial distribution.
VIEWStep 4: Use the calculus to show that p = q by minimising the obtained function.
VIEWStep 5: Determine the value of p for the given data set in the table.
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