Estimation of probability density function of matlab

Matlab probabilistic density function estimate 2016-03-23 16:12:24

Category: C#/.net

Function: ksdensity
Function: estimate the probability density distribution according to the given data
Example:
1. Normal distribution
x = Randn (1,100000);
[Y,xi] = ksdensity (x);
Plot (xi,y, ' Bo ')
% verification
On
Yn=normpdf (xi,0,1); Probability density function for% standard normal distribution
Plot (Xi,yn, ' B ')


2. Rayleigh distribution
x = ABS (RANDN (1,10000) + 1I*RANDN (1,10000));
[Y,xi] = ksdensity (x);
Plot (xi,y, ' Bo ')
% verification
On
b = 1;
Yn = zeros (size (xi));
K=find (B > 0 & XI >= 0);
If any (k),
XK = XI (k);
Probability density function of the% Rayleigh distribution
YP (k) = (xk./b^2). * EXP (-xk.^2./(2*b^2));
End
Plot (XI,YP, ' B ')


3. The distribution of Les?
N = 100000;
K = 0.5;
CONST=1/(k+1);
X1=RANDN (1,n);
X2=RANDN (1,n);
X=sqrt (const* (X1+sqrt (2*k). ^2+x2.^2));
[Y,xi] = ksdensity (x);
Plot (xi,y, ' Bo ')
% verification
On
sig = 1;
v = 1;
Yn = zeros (size (xi));
K=find (B > 0 & XI >= 0);
If any (k),
XK = XI (k);
Percent Rician distribution of probability density functions
YP (k) = (xk./sig^2). * EXP ((-xk.^2 + v.^2)./(2*SIG^2)). * BesselJ (0, (xk. *v./sig^2));
End
Plot (XI,YP, ' B ')
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