Thank you so much for the response. I had NLPNRA in my basic codes that I changed to NLPTR. I will continue working on code to find the problem.  Best regards ... View more

Thanks for the quick response. I appreciate it. I am working with log-likelihood but it cannot be simplified so much. The following shows how it is:   tmp_final = -log( w_0 * tmp_0 + w_1 * tmp_1 + w_2 * tmp_2 + w_3 * tmp_3 + w_4 * tmp_4 ); f = f + tmp_final; end; return ( f ); tmp's contain exponential.    I am not sure why par[2] and tc[1] do not work either. Specifically par[2] should control this overflow problem!     ... View more

Thank you so much. I will. ... View more

Thank you for the response. ... View more

I have a code to obtain MLE. In my code NLPTR is used and I get the correct answers when I implement the code using some of the datasets I have; however, for one of the datasets with 268 subjects, I get zeros for all parameters. I run the same code with the first 75 subjects and get the estimates without any problem but it works with just the first 75 subjects in the dataset I have. I don't see any problem with my data. My function is a complicated function and my data is longitudinal with 4 specific time points. I need to estimate 35 parameters. The Error is "Overflow error in *.". I also try to resolve the problem by controlling overflow but cannot. con = { . . . . . . . . . . 1e-4 1e-4 1e-4 1e-4 1e-4 . . . . . . . . . . . . . . . . . . . . , /* lower bounds */ . . . . . . . . . . . . 0.99 0.99 0.48 . . . . . . . . . . . . . . . . . . . . }; /* upper bounds */ p = { 6.46 0.65 0.34 0.2 0.13 5 0.2 0.3 0.2 0.1 1 1 0.5 0.6 0.4 0 0 0 0 6 9 0.4 0.4 1.09 0.5 0.2 0.5 0.5 0.3 0.06 0.1 0.9 0.7 0.3 1.1 };/* initial guess for solution*/ optn = {1 /* maximum */ 4}; tc=repeat(.,1,13); *tc[1] = 2; tc[12]=1E-3; par=repeat(.,1,10); par[2]=1E-3; DO MC=1 TO N_MC; call NLPTR(rc, result, "LogLik", p, optn, con,tc,par) ; print result; *print rc; Results_all[MC,]=result;  Thank you   ... View more