Can I use the in-built function 'mle' for Maximum Likelihood Estimate that maximizes the log-likelihood of a vector in MATLAB for this purpose?

In my work I have a vector of particular length 'L'. I want to maximize the log-likelihood estimate of the vector using maximum likelihood estimation. I have followed the following procedure:

x=[vector(1:L)];
pd = fitdist(x,'Normal');
z=log(normpdf(x,pd(1),pd(2)); %for finding log-likelihood

However, I do not know whether the above program maximizes the log-likelihood. I am getting a scalar value in 'z', can I use that scalar value to plot back the desired signal? The distribution is assumed to be Normal distribution. Is there any other way to do the problem?

Answer 1

[Torsten]

x=[vector(1:L)];
pd = fitdist(x,'Normal');
nll = negloglik(pd)