least square fitting of multiple variable equation (error: too many input arguments)

I have a data file constituting 2 lines (EXP_x, EXP_y) and want to fit it with the equation mentioned in the second paragraph which has two variables (w, a).

here is the code

EXP=textread('filename')
    global EXP_x
global EXP_y
EXP_x=EXP(:,1);
EXP_y=EXP(:,2);
w0=[0 0.5];
lb=[0 0.5];
ub=[20 2];
x=lsqcurvefit(@distribution,w0,EXP_x,EXP_y,lb,ub);

function calculation=distribution(w,a)
global EXP_x
global EXP_y
gamma=@(t) integral(t.^(w-1).*exp(-t),0,inf);
calculation=(a/((w^(3/2))*gamma)*exp(-(EXP_x/w).^a))
end

it doesn't work. Error: "lsqcurvefit too many input arguments in that case"

If it is not the proper case to use the lsqcurvefit, please tell me the replacement method.

Thank you.

Answer 1

[Torsten]

x=lsqcurvefit(@(w)distribution(w(1),w(2)),w0,EXP_x,EXP_y,lb,ub);

instead of

x=lsqcurvefit(@distribution,w0,EXP_x,EXP_y,lb,ub);

and

function calculation=distribution(w,a)
global EXP_x
global EXP_y
gammah = gamma(w);
calculation=(a/((w^(3/2))*gammah)*exp(-(EXP_x/w).^a))
end

instead of

function calculation=distribution(w,a)
global EXP_x
global EXP_y
gamma=@(t) integral(t.^(w-1).*exp(-t),0,inf);
calculation=(a/((w^(3/2))*gamma)*exp(-(EXP_x/w).^a))
end