负二项式，泊松伽马混合 winbugs

Question

Winbugs trap error

1. • model { for (i in 1:5323) { Y[i] ~ dpois(mu[i]) # NB model as a Poisson-gamma mixture mu[i] ~ dgamma(b[i], a[i]) # NB model as a poisson-gamma mixture a[i] <- b[i] / Emu[i] b[i] <- B * X[i] Emu[i] <- beta0 * pow(X[i], beta1) # model equation } # Priors beta0 ~ dunif(0,10) # parameter beta1 ~ dunif(0,10) # parameter B ~ dunif(0,10) # over-dispersion parameter } X[] Y[] 1.5 0 2.9 0 1.49 0 0.39 0 3.89 0 2.03 0 0.91 0 0.89 0 0.97 0 2.16 0 0.04 0 1.12 1s 2.26 0 3.6 1 1.94 0 0.41 1 2 0 0.9 0 0.9 0 0.9 0 0.1 0 0.88 1 0.91 0 6.84 2 3.14 3 End ```

• This is just a sample of the data, the model question is coming from Ezra Hauer 8.3.2, the art of regression of road safety, the model is providing an **error undefined real result. **

• The aim of model is to fully Bayesian and a one step model and not use empirical bayes.

• The results should be similar to MLE where beta0 is 1.65, beta1 0.871, overdispersion is 0.531

• X is the only variable and y is actual collision, So X cannot be zero or negative, while y cannot be lower than zero, if the model in solved as Poisson gamma mixture using maximum likelihood then it can be created

• How can I make this model work

• Solving an error in winbugs?

Answer 1

the data is in excel, the model worked fine when I selected the biggest 1000 observations only.