Description: fit_ML_rayleigh - Maximum Likelihood fit of the rayleigh distribution of i.i.d. samples!.
Given the samples of a rayleigh distribution, the PDF parameter is found
fits data to the probability of the form:
p(r)=r*exp(-r^2/(2*s))/s
with parameter: s
format: result = fit_ML_rayleigh( x,hAx )
input: x - vector, samples with rayleigh 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
s - fitted parameter
CRB - Cram?r-Rao Bound for the estimator value
RMS - RMS error of the estimation
type- ML
- [rayleigh] - Maximum likelihood estimation for raylei
File list (Check if you may need any files):
fit_ML_rayleigh.m
Download