Dear forum,
I have a vector of parameters that I estimate over time (t1, t2, … tn) based on some longitudinal behavioral data. I have missing data points (let’s say t3 is missing), meaning that in certain time points, my parameters cannot be estimated. MCMC deals with it by imputing the missing parameters values, but what is the case with optimization? How does it deal with missing values?
Thank you!