How Does the Constraint θ ≤ 1/4 Affect the MLE in Bernoulli Trials?

So you need to check the endpoints 0 and 1/4 as well.In summary, to find the MLE of the probability of success θ, which is at most 1/4, in two independent Bernoulli trials with one failure and one success, you can use the likelihood function L(θ) = θ(1-θ) and find the critical point by setting the derivative to zero. However, since the interval is restricted to [0,1/4], you also need to check the endpoints 0 and 1/4 to determine the maximum. The MLE will be at 1/4.
  • #1
SandMan249
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0

Homework Statement


Two independent bernoulli trials resulted in one failure and one success. What is the MLE of the probability of success θ is it is know that θ is at most 1/4


Homework Equations


f(x,θ) = θx (1-θ)1-x


The Attempt at a Solution


Now, I know how to find the likelihood and use it to solve for the MLE. But I am not sure how the "θ is at most 1/4" would factor into the equation.

For a Bernoulli trial: f(x,θ) = θx (1-θ)1-x
L(θ) = θ(1-θ)
L'(θ) = 1-2θ ----> equate to zero
θ(hat) = 1/2 (which is the MLE)

But what do I do about the fact that "θ is at most 1/4"? Please help
 
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  • #2
You're trying to maximize L(θ) on the interval [0,1/4]. Recall a basic calculus fact that the maximum of a function on a closed interval is either a critical point (where the derivative is zero) or an end point
 
  • #3
Thank you.
In this case, since the function is simply: θ(hat) = 1/2 (a constant)
The maximum will lie at 1/4
Correct?
 
  • #4
The critical point is at 1/2. But the function you want to maximize is L(θ) = θ(1-θ)
 

Related to How Does the Constraint θ ≤ 1/4 Affect the MLE in Bernoulli Trials?

What is MLE of Bernoulli trials?

The Maximum Likelihood Estimation (MLE) of Bernoulli trials is a statistical method used to estimate the probability of success in a sequence of independent binary (yes/no) trials. It is based on the likelihood function, which is a measure of how likely the observed data is under a given probability model.

How is MLE of Bernoulli trials calculated?

To calculate the MLE of Bernoulli trials, we first need to define a probability model that represents the data. This is usually done by assuming that the trials are independent and have the same probability of success. Then, the likelihood function is maximized using numerical methods or calculus to find the value of the probability that best explains the observed data.

What are the assumptions of MLE of Bernoulli trials?

The main assumptions of MLE of Bernoulli trials are that the trials are independent and have the same probability of success. Additionally, the trials must be binary (only two possible outcomes) and the sample size should be large enough for the estimates to be accurate.

What is the purpose of MLE of Bernoulli trials?

The purpose of MLE of Bernoulli trials is to estimate the probability of success in a series of independent binary trials. This can be useful in various fields such as medicine, psychology, and market research, where we are interested in understanding the likelihood of a certain outcome.

What are the limitations of MLE of Bernoulli trials?

One of the main limitations of MLE of Bernoulli trials is that it assumes the trials are independent and have the same probability of success. In reality, this may not always be the case. Additionally, the estimates may be inaccurate if the sample size is too small or the data is not representative of the population.

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