1 files changed, 0 insertions, 44 deletions
diff --git a/tests/testthat/test_FOMC_ill-defined.R b/tests/testthat/test_FOMC_ill-defined.R
deleted file mode 100644
index ee3d2b68..00000000
--- a/tests/testthat/test_FOMC_ill-defined.R
+++ /dev/null
@@ -1,44 +0,0 @@
-# Copyright (C) 2016 Johannes Ranke
-# Contact: jranke@uni-bremen.de
-
-# This file is part of the R package mkin
-
-# mkin 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, see <http://www.gnu.org/licenses/>
-
-context("Fitting the FOMC model with large parameter correlation")
-
-# Dataset that I ran across during my work and for which the calculation of the
-# Jacobian failed. Data were slightly fuzzed.
-FOMC_test <- data.frame(
-  name = "test_compound",
-  time = c(0, 14, 31, 59, 91),
-  value = c(45.8, 28.0, 28.5, 35.1, 35.6))
-
-test_that("Fitting with large parameter correlation gives warnings", {
-
-  #skip("Skip test for warnings triggered by large parameter correlation as it failed on r-forge")
-
-  # When fitting from the maximum, the Port algorithm does not converge (with
-  # default settings)
-  expect_warning(
-    fit.FOMC.Port <- mkinfit("FOMC", FOMC_test, method.modFit = "Port"), 
-    "Optimisation by method Port did not converge")
-
-  # When we use Levenberg-Marquardt, we get a problem estimating the Jacobian
-  # for the untransformed model
-  expect_warning(
-    fit.FOMC.Marq <- mkinfit("FOMC", FOMC_test, method.modFit = "Marq"),
-    "Calculation of the Jacobian failed for the cost function of the untransformed model")
-
-})