Nothing
# Load the example dataset
dataset <- list(
"X" = simData[[1]]$X,
"t" = simData[[1]]$time,
"di" = simData[[1]]$status
)
# Run a Bayesian Cox model
## Initial value: null model without covariates
initial <- list("gamma.ini" = rep(0, ncol(dataset$X)))
# Prior parameters
hyperparPooled <- list(
"c0" = 2, # prior of baseline hazard
"tau" = 0.0375, # sd (spike) for coefficient prior
"cb" = 20, # sd (slab) for coefficient prior
"pi.ga" = 0.02, # prior variable selection probability for standard Cox models
"a" = -4, # hyperparameter in MRF prior
"b" = 0.1, # hyperparameter in MRF prior
"G" = simData$G # hyperparameter in MRF prior
)
test_that("burnin must be less than nIter", {
expect_error(BayesSurvive(dataset, Iter = 30, burnin = 30))
})
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