Nothing
test_that("global seed implies same MCMC", {
set.seed(888)
data <- dreamer_data_quad(
n_cohorts = c(10, 10, 10, 10),
dose = c(.25, .5, .75, 1.5),
b1 = 0,
b2 = 2,
b3 = - 1,
sigma = .5
)
set.seed(1)
output1 <- dreamer_mcmc(
data = data,
n_adapt = 1e3,
n_burn = 1e3,
n_iter = 1e3,
n_chains = 2,
silent = TRUE,
mod_linear = model_linear(
mu_b1 = 0,
sigma_b1 = 1,
mu_b2 = 0,
sigma_b2 = 1,
shape = 1,
rate = .001,
w_prior = 1
)
)
set.seed(1)
output2 <- dreamer_mcmc(
data = data,
n_adapt = 1e3,
n_burn = 1e3,
n_iter = 1e3,
n_chains = 2,
silent = TRUE,
mod_linear = model_linear(
mu_b1 = 0,
sigma_b1 = 1,
mu_b2 = 0,
sigma_b2 = 1,
shape = 1,
rate = .001,
w_prior = 1
)
)
expect_identical(output1, output2)
})
test_that("different seeds imply different MCMC", {
set.seed(888)
data <- dreamer_data_quad(
n_cohorts = c(10, 10, 10, 10),
dose = c(.25, .5, .75, 1.5),
b1 = 0,
b2 = 2,
b3 = - 1,
sigma = .5
)
set.seed(1)
output1 <- dreamer_mcmc(
data = data,
n_adapt = 1e3,
n_burn = 1e3,
n_iter = 1e3,
n_chains = 2,
silent = TRUE,
mod_linear = model_linear(
mu_b1 = 0,
sigma_b1 = 1,
mu_b2 = 0,
sigma_b2 = 1,
shape = 1,
rate = .001,
w_prior = 1
)
)
set.seed(2)
output2 <- dreamer_mcmc(
data = data,
n_adapt = 1e3,
n_burn = 1e3,
n_iter = 1e3,
n_chains = 2,
silent = TRUE,
mod_linear = model_linear(
mu_b1 = 0,
sigma_b1 = 1,
mu_b2 = 0,
sigma_b2 = 1,
shape = 1,
rate = .001,
w_prior = 1
)
)
expect_false(identical(output1, output2))
})
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