I'm using the Fit Parametric Survival platform and finding convergence issues with many models that I run. For example, I can use 1 model effect and get convergence, and sometimes I can use 2 model effects (independent variables), but other combinations of 2 model effects will not converge. I don't think I have too many degrees of freedom -- one model that doesn't converge has 11 DF, while another model that does converge (on the same data) has 49DF. What tips are there to address convergence issues?
What distribution are you using to model the errors? What does a plot of the residuals look like?
How much of the data is censored? What kind of censoring happens with your data?
Nothing so far seems unusual or likely the cause for non-convergence. I recommend that you contact JMP Technical Support at email@example.com and ask for help. We encourage users to seek help here but your problem requires technical support.
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