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# Grouped Data 2 Use I(lower,upper) for censoring (not for truncation)

########################################################################

model

{

for (i in 1:14)

{

y1[i] ~ dnorm(mu, tau)I(, height[1]) # likelihood

}

for (i in 1:30)

{

y2[i] ~ dnorm(mu, tau)I(height[1], height[2]) # likelihood

}

for (i in 1:49)

{

y3[i] ~ dnorm(mu, tau)I(height[2], height[3]) # likelihood

}

for (i in 1:70)

{

y4[i] ~ dnorm(mu, tau)I(height[3], height[4]) # likelihood

}

for (i in 1:33)

{

y5[i] ~ dnorm(mu, tau)I(height[4], height[5]) # likelihood

}

for (i in 1:15)

{

y6[i] ~ dnorm(mu, tau)I(height[5],) # likelihood

}

mu ~ dnorm(0, 0.000001) # approximates the improper prior

tau ~ dgamma(0.0001, 0.0001) # approximates the improper prior

sigma <- 1/sqrt(tau)

lsigma <- log(sigma)

}

# Data

list( height = c(66, 68, 70, 72, 74))

# Initial values: load the values below first and then "gen.inits"

list( mu = 70, tau=1 )

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# For scatter plot of mu and lsigma, Inference -> Correlations -> scatter