Estimating Theta for Beta Distribution: Method of Moments vs. MLE?

In summary, the conversation discusses finding an estimator for theta by the method of moments using a given PDF. The first moment of the beta distribution is aligned with the first moment of the sample to solve for theta. The attempt at solving this using MLE also yielded a different estimate for theta.
  • #1
mrkb80
41
0

Homework Statement


Let [itex]X_1,...,X_n [/itex] be iid with pdf [itex]f(x;\theta) = \theta x^{\theta-1} , 0 \le x \le 1 , 0 < \theta < \infty [/itex]

Find an estimator for [itex]\theta[/itex] by method of moments

Homework Equations


The Attempt at a Solution


I know I need to align the first moment of the beta distribution with the first moment of the sample ([itex]\bar{x}[/itex] or [itex]\dfrac{\Sigma_{i=1}^n x_i}{n}[/itex])

The beta distribution has a first moment of [itex]\dfrac{\alpha}{\alpha + \beta}[/itex]I guess my problem is figuring out what my should be alpha and beta from the given pdf, from there it is simply just [itex]\bar{x}=\dfrac{\alpha}{\alpha + \beta}[/itex] and then solving for [itex]\theta[/itex] Any advice?

I did try to take the expected value of the pdf and set it equal to x bar, but I think that is not the correct answer ( I got something like [itex]\hat{\theta}=\dfrac{\bar{x}}{1-\bar{x}}[/itex] )

I also attempted this using MLE and got something like [itex]\hat{\theta}=\dfrac{-n}{\Sigma_{i=1}^n \ln{x_i}} [/itex] but I would also like to solve this problem with method of moments.

Thanks in advance.
 
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  • #2
mrkb80 said:
I know I need to align the first moment of the beta distribution with the first moment of the sample ([itex]\bar{x}[/itex] or [itex]\dfrac{\Sigma_{i=1}^n x_i}{n}[/itex])

The beta distribution has a first moment of [itex]\dfrac{\alpha}{\alpha + \beta}[/itex]


I guess my problem is figuring out what my should be alpha and beta from the given pdf, from there it is simply just [itex]\bar{x}=\dfrac{\alpha}{\alpha + \beta}[/itex] and then solving for [itex]\theta[/itex] Any advice?

I did try to take the expected value of the pdf and set it equal to x bar, but I think that is not the correct answer ( I got something like [itex]\hat{\theta}=\dfrac{\bar{x}}{1-\bar{x}}[/itex] )
If you represent it as a case of a Beta distribution, you get α=θ, β=1, yes? And that gives you the same result as you obtained directly. What makes you think it is wrong?
 
  • #3
Thanks for the reply.

It just felt wrong to me because it was so far from the MLE estimate, but I know that can happen.
 

1. What is the Method of Moments?

The Method of Moments is a statistical method used to estimate the parameters of a probability distribution by equating theoretical moments of the distribution to sample moments.

2. How is the Method of Moments used in the Beta Distribution?

In the Beta Distribution, the Method of Moments is used to estimate the two shape parameters, alpha and beta, by equating the mean and variance of the distribution to the sample mean and variance.

3. Can the Method of Moments be used for any type of data?

The Method of Moments can be used for data that follows a known probability distribution, such as the Beta Distribution. However, it may not be suitable for data that does not fit a known distribution.

4. What are the advantages of using the Method of Moments?

The Method of Moments is a relatively simple and intuitive method that does not require advanced mathematical knowledge. It also produces unbiased estimators and can be used for small sample sizes.

5. Are there any limitations to using the Method of Moments?

The Method of Moments may not be accurate if the underlying distribution is not a good fit for the data. It also assumes that the sample moments and theoretical moments are equal, which may not always be the case.

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