search for: depth2

....R. numbers <- c(1134,956,328,529,435,599,27,99) dim(numbers) <- c(2,2,2) numbers dimnames(numbers)[[3]] <-list("Mussels", "No Mussels") dimnames(numbers)[[2]] <- list("Flow", "No Flow") dimnames(numbers)[[1]] <- list("Depth1", "Depth2") ftable(numbers) as.data.frame.table(numbers) frame <- as.data.frame.table(numbers) names(frame) <- c("wd", "wv", "MP", "Count") frame attach(frame) model1 <- glm(Count~MP+wd+wv,poisson)

Hi, I am running a model with count data and one categorical predictor (simple model for me to understand it fully), I did in R a glm like this: glm(Recruitment~Depth, family=poisson). I get the coefficientes and confidence intervals and all is ok. But then I want to do the same model with Bayesian stats, here is my code: model { for (i in 1:232) { Recruitment[i]~dpois(lambda[i])