set.seed(123)
normal_example <- example_powerscale_model("univariate_normal")
test_that("powerscale functions work for CmdStanFit", {
skip_on_cran()
cs <- cmdstanr::cmdstan_model(
stan_file = cmdstanr::write_stan_file(normal_example$model_code)
)
cfit <- cs$sample(
data = normal_example$data,
refresh = 0,
seed = 123,
iter_sampling = 250,
iter_warmup = 250,
chains = 1
)
expect_s3_class(
create_priorsense_data(
cfit
),
"priorsense_data"
)
expect_s3_class(
powerscale(
x = cfit,
component = "prior",
alpha = 0.8
),
"powerscaled_draws"
)
expect_s3_class(
powerscale(
x = cfit,
component = "likelihood",
alpha = 0.8
),
"powerscaled_draws"
)
expect_s3_class(
suppressWarnings(powerscale_sequence(
x = cfit
)),
"powerscaled_sequence"
)
expect_s3_class(
powerscale_sensitivity(
x = cfit
),
"powerscaled_sensitivity_summary"
)
}
)
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