Re: Error in apollo_estimate when using MDCNEV
Posted: 30 Sep 2022, 09:19
Dear Stephane,
Yes, I have run the MDCEV model before I try to use MDCNEV, base model, model with socio-demographics, model with socio-demographics and other personal traits, the estimations do not return any errors.
The results from the base model are as follows,
LL(start) : -42920.59
LL(0) : Not applicable
LL(C) : Not applicable
LL(final) : -28564.04
Rho-square (0) : Not applicable
Adj.Rho-square (0) : Not applicable
AIC : 57138.08
BIC : 57168.44
Estimated parameters : 5
Time taken (hh:mm:ss) : 00:00:1.56
pre-estimation : 00:00:0.16
estimation : 00:00:1.14
post-estimation : 00:00:0.25
Iterations : 56
Min abs eigenvalue of Hessian : 2e-06
Unconstrained optimisation.
Estimates:
Estimate s.e. t.rat.(0) Rob.s.e. Rob.t.rat.(0)
alpha_base -18.450 667.38779 -0.02765 0.19994 -92.28
gamma_nrfund 272.595 15.07501 18.08256 12.16243 22.41
gamma_rfund 227.371 9.20559 24.69925 7.87553 28.87
delta_nrfund -9.225 0.03689 -250.04542 0.03974 -232.14
delta_rfund -8.007 0.03289 -243.45575 0.03421 -234.03
sigma 1.000 NA NA NA NA
Thank you as always!
Best,
Yadi
Yes, I have run the MDCEV model before I try to use MDCNEV, base model, model with socio-demographics, model with socio-demographics and other personal traits, the estimations do not return any errors.
The results from the base model are as follows,
LL(start) : -42920.59
LL(0) : Not applicable
LL(C) : Not applicable
LL(final) : -28564.04
Rho-square (0) : Not applicable
Adj.Rho-square (0) : Not applicable
AIC : 57138.08
BIC : 57168.44
Estimated parameters : 5
Time taken (hh:mm:ss) : 00:00:1.56
pre-estimation : 00:00:0.16
estimation : 00:00:1.14
post-estimation : 00:00:0.25
Iterations : 56
Min abs eigenvalue of Hessian : 2e-06
Unconstrained optimisation.
Estimates:
Estimate s.e. t.rat.(0) Rob.s.e. Rob.t.rat.(0)
alpha_base -18.450 667.38779 -0.02765 0.19994 -92.28
gamma_nrfund 272.595 15.07501 18.08256 12.16243 22.41
gamma_rfund 227.371 9.20559 24.69925 7.87553 28.87
delta_nrfund -9.225 0.03689 -250.04542 0.03974 -232.14
delta_rfund -8.007 0.03289 -243.45575 0.03421 -234.03
sigma 1.000 NA NA NA NA
Thank you as always!
Best,
Yadi