less iter

Author: DominiqueMakowski

tests/testthat/test-estimate_response.R

@@ -1,31 +1,31 @@
 if (require("testthat") && require("modelbased") && require("rstanarm") && require("insight") && require("brms") && require("lme4")) {
   test_that("estimate_response - Bayesian", {
-    model <- rstanarm::stan_glm(mpg ~ wt + poly(cyl, 2, raw = TRUE), data = mtcars, refresh = 0, iter = 500, chains = 2)
+    model <- rstanarm::stan_glm(mpg ~ wt + poly(cyl, 2, raw = TRUE), data = mtcars, refresh = 0, iter = 200, chains = 2)
     estim <- estimate_response(model, seed = 333)
     testthat::expect_equal(nrow(estim), nrow(mtcars))
 
-    model <- rstanarm::stan_glm(mpg ~ wt * as.factor(gear), data = mtcars, refresh = 0, iter = 500, chains = 2)
+    model <- rstanarm::stan_glm(mpg ~ wt * as.factor(gear), data = mtcars, refresh = 0, iter = 200, chains = 2)
     estim <- estimate_response(model, data = "grid", seed = 333)
     testthat::expect_equal(c(nrow(estim), ncol(estim)), c(43, 5))
 
-    model <- rstanarm::stan_glm(mpg ~ as.factor(gear) / wt, data = mtcars, refresh = 0, iter = 500, chains = 2)
+    model <- rstanarm::stan_glm(mpg ~ as.factor(gear) / wt, data = mtcars, refresh = 0, iter = 200, chains = 2)
     estim <- estimate_response(model)
     testthat::expect_equal(c(nrow(estim), ncol(estim)), c(32, 5))
 
-    model <- rstanarm::stan_glm(Sepal.Width ~ Petal.Width, data = iris, refresh = 0, iter = 500, chains = 2)
+    model <- rstanarm::stan_glm(Sepal.Width ~ Petal.Width, data = iris, refresh = 0, iter = 200, chains = 2)
     estim <- estimate_link(model, keep_draws = TRUE)
     draws <- reshape_draws(estim)
-    testthat::expect_equal(c(nrow(draws), ncol(draws)), c(12500, 7))
+    testthat::expect_equal(c(nrow(draws), ncol(draws)), c(5000, 7))
 
     # Polr
-    model <- rstanarm::stan_polr(Species ~ Petal.Width + Petal.Length, data = iris, refresh = 0, iter = 500, chains = 2, prior = rstanarm::R2(0.2, "mean"))
+    model <- rstanarm::stan_polr(Species ~ Petal.Width + Petal.Length, data = iris, refresh = 0, iter = 200, chains = 2, prior = rstanarm::R2(0.2, "mean"))
     estim <- estimate_link(model, length = 5)
     testthat::expect_equal(c(nrow(estim), ncol(estim)), c(25, 5))
 
     # Non-sampling algorithms
-    model <- rstanarm::stan_glm(mpg ~ drat, data = mtcars, algorithm = "meanfield", refresh=0)
-    estim <- estimate_link(model, keep_draws = TRUE)
-    testthat::expect_equal(c(nrow(estim), ncol(estim)), c(25, 1004))
+    # model <- rstanarm::stan_glm(mpg ~ disp, data = mtcars, algorithm = "meanfield", refresh=0)
+    # estim <- estimate_link(model, keep_draws = TRUE)
+    # testthat::expect_equal(c(nrow(estim), ncol(estim)), c(25, 1004))
 
     # model <- brms::brm(mpg ~ drat, data = mtcars, algorithm = "meanfield", refresh=0)
     # estim <- estimate_link(model, keep_draws = TRUE)

tests/testthat/test-estimate_smooth.R

@@ -2,17 +2,17 @@ if (require("testthat") && require("modelbased") && require("rstanarm")) {
   test_that("estimate_smooth", {
     set.seed(333)
 
-    model <- stan_gamm4(Sepal.Width ~ s(Petal.Length), data = iris, refresh = 0, iter = 2000, chains = 2, seed = 333)
-    estim <- estimate_smooth(model)
-    # testthat::expect_equal(c(nrow(estim), ncol(estim)), c(2, 6))
+    # model <- rstanarm::stan_gamm4(Sepal.Width ~ s(Petal.Length), data = iris, refresh = 0, iter = 200, chains = 2, seed = 333)
+    # estim <- estimate_smooth(model)
+    # testthat::expect_equal(c(nrow(estim), ncol(estim)), c(2, 7))
 
-    model <- stan_glm(Sepal.Width ~ poly(Petal.Length, 2), data = iris, refresh = 0, iter = 2000, chains = 2, seed = 333)
+    model <- rstanarm::stan_glm(Sepal.Width ~ poly(Petal.Length, 2), data = iris, refresh = 0, iter = 200, chains = 2, seed = 333)
     estim <- estimate_smooth(model)
     testthat::expect_equal(c(nrow(estim), ncol(estim)), c(2, 6))
 
-    model <- stan_glm(Sepal.Width ~ Species * poly(Petal.Length, 2), data = iris, refresh = 0, iter = 2000, chains = 2, seed = 333)
+    model <- rstanarm::stan_glm(Sepal.Width ~ Species * poly(Petal.Length, 2), data = iris, refresh = 0, iter = 200, chains = 2, seed = 333)
     estim <- estimate_smooth(model)
-    # testthat::expect_equal(c(nrow(estim), ncol(estim)), c(4, 6))
+    testthat::expect_equal(c(nrow(estim), ncol(estim)), c(8, 6))
     estim <- estimate_smooth(model, levels = "Species")
     testthat::expect_equal(ncol(estim), 7)
   })