load hd188041.dat
A = hd188041(:,8);
n = size(A,1);
plot(sortrows(A),1:n,'*','MarkerSize',2)    %vytvori cummulative distribution function
load hr7575.dat
B = hr7575(:,8);
figure
plot(sortrows(B),1:n,'*','MarkerSize',2)    %vytvori cummulative distribution function
ya = histc(A,-0.08:0.015:0.1);  %rozdeli merania do intervalov
ya(end) = [];
yb = histc(B,-0.05:0.008:0.046);  %rozdeli merania do intervalov
yb(end) = [];
xa = [(-0.08:0.015:0.085)+0.0075]';     %vektor stredov intervalov
xb = [(-0.05:0.008:0.038)+0.004]';      %vektor stredov intervalov

figure
x = xa;  y = ya;    k = size(xa,1);
b0 = [max(y);0;0.05];   %vstupne parametre - je nutne odhadnut ich co najpresnejsie
for i = 1:10    %pocet iteracii, 5 zvycajne staci
    A = b0(1);  %amlituda
    x0 = b0(2);     %stred
    sigma = b0(3);  %polosirka
    G = A*exp(-(x-x0).^2/2/sigma^2);
    X = [G/A,G.*(x-x0)/sigma^2,G.*(x-x0).^2/sigma^3];
    Y=y-G;
    W=eye(k);
    V=X'*W*X;
    U=X'*W*Y;
    b=inv(V)*U;
    b0 = b+b0;  %korekcia parametrov
    plot(x,y,'b',x,G,'r')
    s=sqrt(Y'*W*Y/(k-3));   %standardna odchylka
end

figure
x = xb;  y = yb;    k = size(xb,1);
b0 = [max(y);0;0.01];
for i = 1:10
    A = b0(1);
    x0 = b0(2);
    sigma = b0(3);
    G = A*exp(-(x-x0).^2/2/sigma^2);
    X = [G/A,G.*(x-x0)/sigma^2,G.*(x-x0).^2/sigma^3];
    Y=y-G;
    W=eye(k);
    V=X'*W*X;
    U=X'*W*Y;
    b=inv(V)*U;
    b0 = b+b0;
    plot(x,y,'b',x,G,'r')
    s=sqrt(Y'*W*Y/(k-3));
end