fit_ML_maxwell

   fit_ML_normal - Maximum Likelihood fit of the log-normal distribution of i.i.d. samples!. Given the samples of a log-normal distribution, the PDF parameter is found fits data to the probability of the form: p(x) = sqrt(1/(2*pi))/(s*x)*exp(- (log(x-m)^2)/(2*s^2)) with parameters: m,s format: result = fit_ML_log_normal( x,hAx ) input: x - vector, samples with log-normal distribution to be parameterized hAx - handle of an axis, on which the fitted distribution is plotted if h is given empty, a figure is created. output: result - structure with the fields m,s - fitted parameters CRB_m,CRB_s - Cram?r-Rao Bound for the estimator value RMS - RMS error of the estimation type - ML