Fitting Large Data Sets

I normally deal with rather large data sets (i.e. 700x1600x500 complex valued cubes). Often, I want to fit one of the dimensions at each point (cube(x,y,:) -> lsqcurvefit(@fun, z0, zAxis, zData)). Is there a good way to consolidate and vectorize this process through MeshGrids or something similar? Right now I just use a nested for loop over x and y /*cringing*/. Was wondering if anyone has a clever trick for dealing with this.

for x = 1:size(data, 1)
   for y = 1:size(data, 2)
      zData = squeeze(abs(data(x,y,:)));
      fun = @(p, zAxis) p(1)*exp(-zAxis/p(2));  %or your favorite function
      z0 = [1 1];
      fitResult = lsqcurvefit(fun, z0, zAxis, zData);
      %disp(fitResult)
   end
end

It's just screaming at me that matlab has to have some more efficient way of doing this.

Thanks