The Monte Carlo of the mean square error of the maximum likelihood estimates I try to get mean square error of the maximum likelihood estimators in R (using Monte Carlo).
I can write the calculation for the MLE that is repeated once, but I need to repeat the Monte Carlo calculation many times.

Hint: Embed it in a loop where you change the random seed in each iteration to generate a different sample. Store the estimates from each iteration in vectors. Subtract the true values from the vectors. Obtain the MSEs of the resulting vectors.
