Hi Mustafa,
The mle function uses the “fminsearch” or “fmincon” options to maximise the mle parameters iteratively. The ”start” parameter refers to the initial set of values for the parameters and it changes with every step of the optimization process. A poor choice of starting point can cause mle to converge to a local optimum that is not the global maximum, or to fail to converge entirely.
Since the dataset generated by picking random samples from a Weibull distribution, the optimization leads us to the proper estimates irrespective of the initial condition. However, if we try to fit Weibull distribution to any arbitrary data, this might cause problems to achieve convergence.
You can refer to the following links for further help:
Regards,
Pratyush.
