How to perform the maximum like ratio test?

Hi,

I have to test if my data have a gaussian or a double gaussian behaviour with the MAXIMUM LIKELIHOOD RATIO TEST. I have a problem defining a double gaussian and use it as a pdf. The data are composed by an histogram. I normalized it so that the integral is <=1 Below a possible code:

>> data_norm = normrnd(0,1,1000,1);

>> data = hist(data_norm,14);

>> x = 1:14;

>> figure;

>> plot(x,data);

>> data = data/sum(data); % normalize to unit length. Sum of h now will be 1.

>> figure;

>> plot(x,data)

>> Gauss_mle = mle(data);

>> Double_gauss_pdf=@(sigma1,mu1,sigma2,mu2) ((1/sqrt(2*pi*sigma1^2)*exp((x-mu1).^2/(2*sigma1^2))+1/sqrt(2*pi*sigma2^2)*exp((x-mu2).^2/(2*sigma2^2))));

>> Double_gauss_mle = mle(data,'pdf',Double_gauss_pdf,'start',[0;1;0;1]);

When I compute Double_gauss_mle it gives me:

Error using mlecustom (line 166)

Error evaluating the user-supplied pdf function '@(sigma1,mu1,sigma2,mu2)((1/sqrt(2*pi*sigma1^2)*exp((x-mu1).^2/(2*sigma1^2))+1/sqrt(2*pi*sigma2^2)*exp((x-mu2).^2/(2*sigma2^2))))'.

Error in mle (line 229) phat = mlecustom(data,varargin{:});

Caused by:

    Error using @(sigma1,mu1,sigma2,mu2)((1/sqrt(2*pi*sigma1^2)*exp((x-mu1).^2/(2*sigma1^2))+1/sqrt(2*pi*sigma2^2)*exp((x-mu2).^2/(2*sigma2^2))))
    Too many input arguments.

I also do not know exactly how to proceed once I have the maximum likelihood estimate.

Thank you in advance.