Missed test file commit

Author: andrjohns

tests/testthat/test_stan_lm.R

@@ -1,16 +1,16 @@
 # Part of the rstanarm package for estimating model parameters
 # Copyright (C) 2015, 2016, 2017 Trustees of Columbia University
-# 
+#
 # This program is free software; you can redistribute it and/or
 # modify it under the terms of the GNU General Public License
 # as published by the Free Software Foundation; either version 3
 # of the License, or (at your option) any later version.
-# 
+#
 # This program is distributed in the hope that it will be useful,
 # but WITHOUT ANY WARRANTY; without even the implied warranty of
 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 # GNU General Public License for more details.
-# 
+#
 # You should have received a copy of the GNU General Public License
 # along with this program; if not, write to the Free Software
 # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
@@ -24,7 +24,7 @@ ITER <- 400
 threshold <- 0.21
 REFRESH <- 0
 
-SW(fit <- stan_lm(mpg ~ ., data = mtcars, prior = R2(location = 0.75), 
+SW(fit <- stan_lm(mpg ~ ., data = mtcars, prior = R2(location = 0.75),
                   chains = CHAINS, iter = ITER, seed = SEED, refresh = 0))
 
 
@@ -36,12 +36,12 @@ test_that("stan_aov returns expected result for npk example", {
     K = "contr.poly"
   )
   SW(fit <- stan_aov(yield ~ block + N*P*K, data = npk, contrasts = contrasts_list,
-                     prior = R2(0.5), chains = CHAINS, iter = ITER, seed = SEED, 
+                     prior = R2(0.5), chains = CHAINS, iter = ITER, seed = SEED,
                      refresh = 0))
   expect_stanreg(fit)
-  
+
   fit_sigma <- fit$stan_summary["sigma", "mean"]
-  lm_sigma <- summary(lm(yield ~ block + N*P*K, data = npk, 
+  lm_sigma <- summary(lm(yield ~ block + N*P*K, data = npk,
                          contrasts = contrasts_list))$sigma
   expect_equal(fit_sigma, lm_sigma, tol = threshold)
   expect_output(print(fit), regexp = "stan_aov")
@@ -70,27 +70,27 @@ test_that("stan_biglm returns expected result", {
   y <- mtcars$mpg
   ybar <- mean(y)
   s_y <- sd(y)
-  SW(post <- stan_biglm(biglm, xbar, ybar, s_y, prior = R2(0.5), 
+  SW(post <- stan_biglm(biglm, xbar, ybar, s_y, prior = R2(0.5),
                         chains = CHAINS, iter = ITER, seed = SEED, refresh = 0))
-  expect_equal(coef(lm(mpg ~ wt + qsec + am, data = mtcars)), 
+  expect_equal(coef(lm(mpg ~ wt + qsec + am, data = mtcars)),
                rstan::summary(post)$summary[1:4, "mean"], tol = threshold)
 })
 
 test_that("stan_lm returns expected result for mtcars example", {
   # example using mtcars dataset
   expect_stanreg(fit)
-  
+
   fit_sigma <- fit$stan_summary["sigma", "mean"]
   lm_sigma <- summary(lm(mpg ~ ., data = mtcars))$sigma
   expect_equal(fit_sigma, lm_sigma, tol = threshold)
 })
 test_that("stan_lm returns expected result for trees example", {
   # example using trees dataset
-  SW(fit <- stan_lm(log(Volume) ~ log(Girth) + log(Height), data = trees, 
+  SW(fit <- stan_lm(log(Volume) ~ log(Girth) + log(Height), data = trees,
                   prior = R2(location = 0.9, what = "mean"), refresh = 0,
                   chains = CHAINS, iter = ITER, seed = SEED, adapt_delta = 0.999))
   expect_stanreg(fit)
-  
+
   fit_sigma <- fit$stan_summary["sigma", "mean"]
   lm_sigma <- summary(lm(log(Volume) ~ log(Girth) + log(Height),data = trees))$sigma
   expect_equal(fit_sigma, lm_sigma, tol = threshold)
@@ -101,7 +101,7 @@ test_that("stan_lm doesn't break with less common priors", {
   SW(fit <- stan_lm(mpg ~ -1 + ., data = mtcars, prior = NULL,
                 iter = 10, chains = 1, seed = SEED, refresh = 0))
   expect_stanreg(fit)
-  
+
   # prior_intercept = normal()
   SW(fit <- stan_lm(mpg ~ ., data = mtcars, refresh = 0,
                  prior = R2(0.75), prior_intercept = normal(),
@@ -110,34 +110,34 @@ test_that("stan_lm doesn't break with less common priors", {
 })
 
 test_that("stan_lm doesn't break with vb algorithms", {
-  SW(fit <- stan_lm(mpg ~ ., data = mtcars, 
+  SW(fit <- stan_lm(mpg ~ ., data = mtcars,
                  prior = R2(location = 0.75), refresh = 0,
                  algorithm = "meanfield", seed = SEED))
   expect_stanreg(fit)
-  
+
   SW(fit2 <- update(fit, algorithm = "fullrank"))
   expect_stanreg(fit2)
 })
 
 test_that("stan_lm throws error if only intercept", {
-  expect_error(stan_lm(mpg ~ 1, data = mtcars, prior = R2(location = 0.75)), 
+  expect_error(stan_lm(mpg ~ 1, data = mtcars, prior = R2(location = 0.75)),
                regexp = "not suitable for estimating a mean")
 })
 
 test_that("stan_lm throws error if 'location' is a vector", {
-  expect_error(stan_lm(mpg ~ ., data = mtcars, prior = R2(location = c(0.25, 0.5))), 
+  expect_error(stan_lm(mpg ~ ., data = mtcars, prior = R2(location = c(0.25, 0.5))),
                regexp = "only accepts a single value for 'location'")
 })
 
 test_that("stan_lm throws error if N < K", {
   # NOTE: remove this test once N < K is enabled
-  expect_error(stan_lm(mpg ~ ., data = mtcars[1:5, ], prior = R2(0.75)), 
+  expect_error(stan_lm(mpg ~ ., data = mtcars[1:5, ], prior = R2(0.75)),
                regexp = "more predictors than data points is not yet enabled")
 })
 
 test_that("stan_lm throws error if glmer syntax used", {
-  expect_error(stan_lm(mpg ~ wt + (1|cyl), data = mtcars, 
-                       prior = R2(0.5, "mean")), 
+  expect_error(stan_lm(mpg ~ wt + (1|cyl), data = mtcars,
+                       prior = R2(0.5, "mean")),
                regexp = "model formula not allowed")
 })
 
@@ -149,6 +149,7 @@ test_that("loo/waic for stan_lm works", {
 })
 
 test_that("posterior_predict compatible with stan_lm", {
+  skip_on_os("mac")
   check_for_pp_errors(fit)
   expect_linpred_equal(fit)
 })