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 -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