How to write the code for the following problem?

There are 25 columns in a given dataset each having 10000 points of the form - x(n) = A + w(n) where w(n) ~ N(0,A) AWGN.

1. Estimate A' using maximum likelihood estimation.

2. Using Monte carlo simulations find E(A') and var (A').

3. Plot (E(A')-A)^2 and var(A') as function of N. 4. Find pdf of A'. Plot for N= 5,10,20. Take any of N columns.

[Ankit]

it would be great if you post the problem you are facing during implementation instead of asking for complete solution

[RITAM Ghosh]

I tried to use the phat=mle(data, 'distribution' , dist) function but I'm not sure how A' can be found fron that. Also will this function directly give me the expectation and the variance?