[Gretl-users] MLE estimation N/A std errors even when based on Outer product matrix

Gretl 2020a windows 64bit. Consider the following output from mle estimation (pay attention to the Gradient values and the NA std errors): << --- FINAL VALUES: loglikelihood = -1241.43371416 (steplength = 6.5536e-012) Parameters:       1.3798      1.0173     0.96596 3.7418e-012 Gradients:        2.4007      6.7772     -5.3557    -0.89559 (norm 1.96e+000) Tolerance = 1.81899e-012 Function evaluations: 273 Evaluations of gradient: 39 Model 2: ML, using observations 1-1000 logl = check ? obsll :NA Standard errors based on Outer Products matrix                estimate     std. error   z    p-value   ---------------------------------------------------   const      1.37979            NA       NA     NA   X1         1.01730               NA       NA     NA   sv         0.965960           NA       NA     NA   su         3.74177e-012       NA       NA     NA Warning: norm of gradient = 1.96088 I have a question, and  a suspicion about what the answer might be. My question is: since the Std errors are based on the Outer Products matrix, why are they not computed/presented ? Never mind whether this is a successful estimation attempt -it is not. My question is "mechanical". I would understand "NA" if I was asking for std errors based on the inverted Hessian. But where is the problem in computing std errors based on the gradient? My suspicion: maybe gretl in all cases dutifully computes the full variance expression, [G= likelihood gradient], namely Variance = E(GG') - E(G)E(G)'  (using sample means), i.e. it does not a priori treat as given that E(G)=0. Then, if it so happens that E(G) >> 0 (as is my case), the full expression may become negative, in which case std errors are reported as NA since they are the square root of the variance. Somebody please? -- Alecos Papadopoulos PhD Athens University of Economics and Business web: alecospapadopoulos.wordpress.com/ skype:alecos.papadopoulos