jags.chaindens: Kernel density of each MCMC chain of selected parameters from...

In mbtyers/jagsplot: Diagnostic plotting tools for R2jags output

Description

Kernel density of each MCMC chain of selected parameters from an R2jags object.

Usage

jags.chaindens(jags.out, which.param = NULL, remove.outliers = F)

Arguments

jags.out	A jags output object from R2jags
which.param	A vector of the parameter indices we're interested in plotting. Calling jags.names() first can help with this.
remove.outliers	Whether to truncate the plotting window to the middle 95 percent of the posteriors. Defaults to FALSE.

Author(s)

Matt Tyers

Examples

# ------------ a sample R2jags model ----------- #

## Not run: 
library(R2jags)
N <- 1000
x <- 1:N
epsilon <- rnorm(N, 0, 1)
y <- x + epsilon

cat('model {
 for (i in 1:N){
   y[i] ~ dnorm(y.hat[i], tau)
   y.hat[i] <- a + b * x[i]
}
a ~ dnorm(0, .0001)
b ~ dnorm(0, .0001)
tau <- pow(sigma, -2)
sigma ~ dunif(0, 100)
}', file="test.jags")

test.data <- list(x=x,y=y,N=N)
test.jags.out <- jags(model.file="test.jags", data=test.data, 
     parameters.to.save=c("a","b","tau","sigma"), n.chains=3, n.iter=1000)

# ------------- calling jags.dens() ------------ #
par(mfrow=c(3,2))
jags.chaindens(test.jags.out)

# say we're only interested in parameters a and b
jags.names(test.jags.out)
par(mfrow=c(2,1))
jags.chaindens(test.jags.out,which.param=1:2)

## End(Not run)

mbtyers/jagsplot documentation built on May 22, 2019, 12:58 p.m.