I am running a Pradel model with random effects on p for a robust design data set spanning 12 years with 3-8 annual capture occasions. My estimates for phi, sigmap, p, and c are all reasonable with good standard errors but I get a "numerical underflow" warning. This happens even when the model is heavily constrained (dot models). The message goes away when I set sigmap=0. What causes this and should I be concerned? Thanks!!!
Joe