https://github.com/cran/bayestestR
Tip revision: 428249f43a9c6fd0c425b28deb5fee51a9525d69 authored by Dominique Makowski on 18 September 2022, 01:46:03 UTC
version 0.13.0
version 0.13.0
Tip revision: 428249f
test-bayesfactor_restricted.R
if (require("testthat")) {
# bayesfactor_restricted data.frame ---------------------------------------
test_that("bayesfactor_restricted df", {
prior <- data.frame(
X = distribution_normal(100),
X1 = c(distribution_normal(50), distribution_normal(50)),
X3 = c(distribution_normal(80), distribution_normal(20))
)
posterior <- data.frame(
X = distribution_normal(100, .4, .2),
X1 = distribution_normal(100, -.2, .2),
X3 = distribution_normal(100, .2)
)
hyps <- c(
"X > X1 & X1 > X3",
"X > X1"
)
bfr <- bayesfactor_restricted(posterior, hypothesis = hyps, prior = prior)
expect_equal(bfr$p_prior, c(0.2, 0.5), tolerance = 0.1)
expect_equal(bfr$p_posterior, c(0.31, 1), tolerance = 0.1)
expect_equal(bfr$log_BF, c(0.43, 0.69), tolerance = 0.1)
expect_equal(exp(bfr$log_BF), bfr$p_posterior / bfr$p_prior, tolerance = 0.1)
expect_error(bayesfactor_restricted(posterior, prior, hypothesis = "Y < 0"))
})
# bayesfactor_restricted RSTANARM -----------------------------------------
test_that("bayesfactor_restricted RSTANARM", {
skip_on_cran()
skip_if_not_installed("rstanarm")
suppressWarnings(
fit_stan <- rstanarm::stan_glm(mpg ~ wt + cyl + am, data = mtcars, refresh = 0, iter = 200)
)
hyps <- c(
"am > 0 & cyl < 0",
"cyl < 0",
"wt - cyl > 0"
)
set.seed(444)
fit_p <- suppressMessages(unupdate(fit_stan))
bfr1 <- bayesfactor_restricted(fit_stan, prior = fit_p, hypothesis = hyps)
set.seed(444)
bfr2 <- bayesfactor_restricted(fit_stan, hypothesis = hyps)
expect_equal(bfr1, bfr2)
})
}