if (require("BayesFactor", quietly = TRUE)) { test_that("weighted_posteriors for BayesFactor", { skip_on_cran() set.seed(123) # compute Bayes Factor for 31 different regression models null_den <- regressionBF(mpg ~ cyl + disp + hp + drat + wt, data = mtcars, progress = FALSE ) wBF <- weighted_posteriors(null_den) expect_s3_class(wBF, "data.frame") expect_equal( attr(wBF, "weights")$weights, c( 0, 13, 9, 0, 0, 55, 11, 4, 4, 1246, 6, 2, 38, 4, 946, 12, 3, 3, 209, 3, 491, 174, 4, 134, 7, 293, 1, 123, 35, 92, 51, 27 ) ) }) test_that("weighted_posteriors for BayesFactor (intercept)", { set.seed(123) # fails for win old-release skip_on_cran() skip_on_ci() dat <- data.frame( x1 = rnorm(10), x2 = rnorm(10), y = rnorm(10) ) BFmods <- regressionBF(y ~ x1 + x2, data = dat, progress = FALSE) res <- weighted_posteriors(BFmods) expect_equal(attr(res, "weights")$weights, c(1032, 805, 1388, 775)) wHDI <- hdi(res[c("x1", "x2")], ci = 0.9) expect_equal(wHDI$CI_low, c(-0.519, -0.640), tolerance = 0.01) expect_equal(wHDI$CI_high, c(0.150, 0.059), tolerance = 0.01) }) test_that("weighted_posteriors for nonlinear BayesFactor", { set.seed(123) data(sleep) BFS <- ttestBF( x = sleep$extra[sleep$group == 1], y = sleep$extra[sleep$group == 2], nullInterval = c(-Inf, 0), paired = TRUE ) res <- weighted_posteriors(BFS) expect_equal(attributes(res)$weights$weights, c(113, 3876, 11)) }) } .runThisTest <- Sys.getenv("RunAllbayestestRTests") == "yes" if (.runThisTest) { if (require("brms", quietly = TRUE)) { test_that("weighted_posteriors vs posterior_average", { skip_on_cran() fit1 <- brm(rating ~ treat + period + carry, data = inhaler, refresh = 0, silent = TRUE, save_pars = save_pars(all = TRUE) ) fit2 <- brm(rating ~ period + carry, data = inhaler, refresh = 0, silent = TRUE, save_pars = save_pars(all = TRUE) ) set.seed(444) expect_warning(res_BT <- weighted_posteriors(fit1, fit2)) set.seed(444) res_brms <- brms::posterior_average(fit1, fit2, weights = "bma", missing = 0) res_brms <- res_brms[, 1:4] res_BT1 <- eti(res_BT) res_brms1 <- eti(res_brms) expect_equal(res_BT1$Parameter, res_brms1$Parameter) expect_equal(res_BT1$CI, res_brms1$CI) expect_equal(res_BT1$CI_low, res_brms1$CI_low) expect_equal(res_BT1$CI_high, res_brms1$CI_high) # plot(res_brms1) # plot(res_BT1) }) } }