I would like to know:
Is $\beta$ a MLE?
If yes what is the mean of it: $E(\beta)=$?
given:
$x$ is a random variable
$$f(x)=\sqrt{\frac{2}{\pi \theta^2}}\exp \left(-\frac{x^2}{2\theta^2}\right)$$ with $\theta,x>0$
I got $\beta = \sqrt{\sum x_i^2/n}$
Doing the likelihood function and the first derivative however when I check the 2nd derivative it was not evident to be negative.
If anyone could help I would appreciate a lot!
I will not get into much detail. As pointed out the first order condition leads to the estimator $$ \hat{\theta} = \sqrt{\frac{\sum_{i = 1}^n x_i^2}{n}} $$ The second order condition leads to $$ \frac{n}{\theta^2} - \frac{3}{\theta^4} \sum_{i = 1}^n x_i^2 $$ Upon substituion of $\hat{\theta}$, this becomes $$ - \frac{2 n^2}{\sum_{i = 1}^n x_i^2} < 0 $$ which is what needed to be verified.