# Create some data
data <- Data(x = c(0.1, 0.5, 1.5, 3, 6, 10, 10, 10),
y = c(0, 0, 0, 0, 0, 0, 1, 0),
cohort = c(0, 1, 2, 3, 4, 5, 5, 5),
doseGrid = c(0.1, 0.5, 1.5, 3, 6,
seq(from = 10, to = 80, by=2)))
# Initialize a model
model <- LogisticLogNormal(mean = c(-0.85, 1),
cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
refDose = 56)
# Get posterior for all model parameters
options <- McmcOptions(burnin = 100,
step = 2,
samples = 2000)
set.seed(94)
samples <- mcmc(data, model, options)
# now extract the alpha0 samples (intercept of the regression model)
alpha0samples <- get(samples, "alpha0")
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