Need to use greta.multivariate. This model and model evolving saved for later.
# make fake data n_species <- 1 n_sites <- 50 n_obs <- 10 occupancy <- matrix(rbinom(n_sites * n_obs, 1, 0.5), nrow = n_sites)
#### constant occupancy detection model #### psi ~ dunif(0,1) p ~ dunif(0,1) for(i in 1:n.sites){ z[i] ~ dbern(psi) #occupancy p.eff[i] <- z[i] * p #detectability for(j in 1:n.reps){ y[i,j] ~ dbern(p.eff[i]) } } # load greta library(greta) # data Y <- as_data(occupancy) # variables psi <- uniform(0,1) # average detectability p <- uniform(0,1) # average occupancy z <- bernoulli(psi) # true occupancy p.eff <- z %*% p #detectability distribution(Y) = bernoulli(p.eff) # create model object with the things we want samples of m <- model(psi, p) # plot model structure plot(m) fit <- mcmc(m)
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