jags_logit {BayesPostEst} | R Documentation |
Fitted JAGS logit model
Description
A fitted JAGS logit model generated with [R2jags::jags()]. See the example code below for how it was created. Used in examples and for testing.
Usage
jags_logit
Format
A class "rjags" object created by [R2jags::jags()]
Examples
if (interactive()) {
data("sim_data")
## formatting the data for jags
datjags <- as.list(sim_data)
datjags$N <- length(datjags$Y)
## creating jags model
model <- function() {
for(i in 1:N){
Y[i] ~ dbern(p[i]) ## Bernoulli distribution of y_i
logit(p[i]) <- mu[i] ## Logit link function
mu[i] <- b[1] +
b[2] * X1[i] +
b[3] * X2[i]
}
for(j in 1:3){
b[j] ~ dnorm(0, 0.001) ## Use a coefficient vector for simplicity
}
}
params <- c("b")
inits1 <- list("b" = rep(0, 3))
inits2 <- list("b" = rep(0, 3))
inits <- list(inits1, inits2)
## fitting the model with R2jags
set.seed(123)
jags_logit <- R2jags::jags(data = datjags, inits = inits,
parameters.to.save = params, n.chains = 2,
n.iter = 2000, n.burnin = 1000, model.file = model)
}
[Package BayesPostEst version 0.3.2 Index]