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Hi all, I am trying to estimate few parameters using the constained maximum likelihood in R and more specifically the constOptim() from the stata package in R. I am programming in Python and using R via the RPy2. In my model, I am assuming that the data follow the Beta-distribution, so I created a simulated dataset by using prespecified values for the parameters and now I am trying to estimate these parameters in order to v...

...ordinal regression data. So my objective function is the likelihood function but is not exactly the entropy function due to the fact that order of the labels matters in my application. Or I'm better of to write my own function? 2. If I need to write my own function, I could see that I can use constOptim to help me maximize my likelihood. Another question here is how can I pass analytical gradient function of each of my network weight into the function? Specifically, my question is that does my gradient function has to be flat representation of each parameter like the following arbitrary example:...

Dear Friends. I found something very puzzling with constOptim(). When I change the parameters for ConstrOptim, the error messages do not seem to be consistent with each other: > constrOptim(c(0.5,0.3,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci) Error in constrOptim(c(0.5, 0.3, 0.5), f = fit.error, gr = fit.error.grr, : initial value not feas...