I am using PROC FMM in SAS, in attempt to use hurdle models on a data set with many zeros. There is one response variable and it's continuous, there are ~90 predictors (continuous - but contain many zeros) and roughly 160 000 records. When I tried running this procedure, I was told
"WARNING: Dual Quasi-Newton optimization cannot be completed. NOTE: The Dual Quasi-Newton optimization technique needs more than 200 iterations or 2000 function calls. Error: No final model fitted because no 'best' model can be determined."
I then tried this same process with fewer variables and the optimization process worked (I think). What possible reasons could there be for this? Additionally, does anyone recommend other prediction/discrimination techniques to use in heavy zero data sets?