1. For the closed simulation example
Modify the simulation code to simulate p0 as varying randomly among individuals according to logit(p0)~Normal(mu=logit(0.5),sigma=1)
Create an additional random effects JAGS model following the above process to estimate mu and sigma as hyperparameters. Caution: you will need to put sensible priors on mu and especially sigma!
With the simulated data compare the default (p0 fixed) and p0 random effects model via DIC. Compare estimate of D
2. For the coyote open SCR example
Create an additional model in which phi and gamma are constant over time (note: S[t] and G[t] will still vary because interval lengths vary)
Compare via DIC fit of these 2 models to the coyote data.
Compare estimates of phi, gamma, and D