use of nonlinear curve fitting with Monte-Carlo analysis

Hi, I am trying to fit a non-linear model with experimental data and also want to run Monte-Carlo analysis with that but it seems very difficult. please help me in this regard. Thank you

temp=[24.88503903
78.50497273
139.9636403
194.6529783
297.4975938
397.283713
];
yieldstress=[45.00727678
36.79417319
37.5451424
33.05702304
30.41701789
28.98254504
];
nsample=1000;
for i=1:nsample
  DD=1e12+2e12*randn(1);
  self_coff=0.08+0.04*randn(1);
  line_energy=0.5+0.5*randn(1);
  conversion_factor=0.32+0.06*randn(1);
  threshold_stress=25.9e9*2.86e-10.*sqrt(DD).*((0.5.*line_energy)+sqrt(self_coff));
  ave_strainrate=2.86e-10*1e12.*sqrt(DD);

    fun(i) =@(x,xdata)threshold_stress+(x(1).*0.89).*(1-((((8.617e-5.*temp)./x(2).*log(6.667e- 
     4./ave_strainrate)).^(1/1.5)).^(1/0.6667)))./(conversion_factor);
     x0 = [1.8 4];
     [x,resnorm,~,exitflag,output]=lsqcurvefit(fun(i),x0,temp,yieldstress);
     end