How to fit a data with mixture of gaussian distribution?

I have a failure data, and i am trying to find the best probability distribution to fit this data.

I try many PDF like generalized extreme value, normal , weibull,...etc. but i couldn't apply mixture gaussians distribution.

I use this code

 [ndata text alldata] = xlsread('battery2.xlsx','li ion');      
[R2,C2]=size(alldata);
Life = ndata(:,72);
A=round(Life);  
[val,idxC, idxV] = unique(A);
n = accumarray(idxV,1);     
m= [n idxC] ;     
y = [val n];
binWidth = 1;         
binCtrs = 0:binWidth:134
counts = hist(Life,binCtrs);
nu = length(Life);
prob = counts / (nu * binWidth);
h4= figure;
bar(binCtrs,prob,'hist');
paramEstsmg = gmdistribution.fit(Life,5); %estimate parameter
xgrids = linspace(0,135,100);   % extend the x-axis     
pdfEstsmg = pdf(paramEstsmg,xgrids); hold on;
line(xgrids,pdfEstsmg,'color','r', 'LineWidth',2)
xzero= cdf.inv(0.01,paramEstsmg);  %inverse cumulative distribution function
yzero=0;

after running the code i got this error:

 Error using checkdata (line 18)
X must be a matrix with 1 columns.
Error in gmdistribution/pdf (line 18)
checkdata(X,obj);
Error in Li_ion_mixture_gaussian (line 71)
pdfEstsmg = pdf(paramEstsmg,xgrids);

This is the generalized extreme value best fit i tried. which works well

any help!! Thanks in advance.

[Amr Hashem]

SOS, any help guys!!