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-rw-r--r--tests/figs/deps.txt2
-rw-r--r--tests/figs/evaluations-according-to-2015-nafta-guidance/plot-nafta-analysis.svg2
-rw-r--r--tests/figs/plotting/mkinparplot-for-focus-c-sfo.svg48
-rw-r--r--tests/testthat/DFOP_FOCUS_C_messages.txt444
-rw-r--r--tests/testthat/FOCUS_2006_D.csf2
-rw-r--r--tests/testthat/NAFTA_SOP_Appendix_B.txt21
-rw-r--r--tests/testthat/NAFTA_SOP_Appendix_D.txt25
-rw-r--r--tests/testthat/summary_DFOP_FOCUS_C.txt48
-rw-r--r--tests/testthat/test_FOCUS_D_UBA_expertise.R7
-rw-r--r--tests/testthat/test_FOCUS_chi2_error_level.R3
-rw-r--r--tests/testthat/test_error_models.R17
-rw-r--r--tests/testthat/test_from_max_mean.R12
-rw-r--r--tests/testthat/test_mkinfit_errors.R24
-rw-r--r--tests/testthat/test_nafta.R4
-rw-r--r--tests/testthat/test_plots_summary_twa.R4
-rw-r--r--tests/testthat/test_schaefer07_complex_case.R9
16 files changed, 407 insertions, 265 deletions
diff --git a/tests/figs/deps.txt b/tests/figs/deps.txt
index 0f6c3754..059d3572 100644
--- a/tests/figs/deps.txt
+++ b/tests/figs/deps.txt
@@ -1,3 +1,3 @@
- vdiffr-svg-engine: 1.0
-- vdiffr: 0.3.0.9000
+- vdiffr: 0.3.0
- freetypeharfbuzz: 0.2.5
diff --git a/tests/figs/evaluations-according-to-2015-nafta-guidance/plot-nafta-analysis.svg b/tests/figs/evaluations-according-to-2015-nafta-guidance/plot-nafta-analysis.svg
index 58f57e93..5e98487b 100644
--- a/tests/figs/evaluations-according-to-2015-nafta-guidance/plot-nafta-analysis.svg
+++ b/tests/figs/evaluations-according-to-2015-nafta-guidance/plot-nafta-analysis.svg
@@ -283,7 +283,7 @@
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diff --git a/tests/figs/plotting/mkinparplot-for-focus-c-sfo.svg b/tests/figs/plotting/mkinparplot-for-focus-c-sfo.svg
index c6a19428..ab517c96 100644
--- a/tests/figs/plotting/mkinparplot-for-focus-c-sfo.svg
+++ b/tests/figs/plotting/mkinparplot-for-focus-c-sfo.svg
@@ -13,17 +13,17 @@
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@@ -34,10 +34,10 @@
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@@ -50,17 +50,17 @@
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@@ -71,11 +71,11 @@
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diff --git a/tests/testthat/DFOP_FOCUS_C_messages.txt b/tests/testthat/DFOP_FOCUS_C_messages.txt
index 7abde0b6..5327b3f6 100644
--- a/tests/testthat/DFOP_FOCUS_C_messages.txt
+++ b/tests/testthat/DFOP_FOCUS_C_messages.txt
@@ -1,148 +1,148 @@
-parent_0 log_k1 log_k2 g_ilr
+parent_0 log_k1 log_k2 g_ilr sigma
85.1 -2.302585 -4.60517 0
-Model cost at call 1 : 7391.39
+Negative log-likelihood at call 1: 7391.39
85.1 -2.302585 -4.60517 0
85.1 -2.302585 -4.60517 0
-Model cost at call 3 : 7391.389
+Negative log-likelihood at call 3: 7391.389
85.1 -2.302585 -4.60517 0
-Model cost at call 4 : 7391.389
+Negative log-likelihood at call 4: 7391.389
85.1 -2.302585 -4.60517 1.490116e-08
85.06371 -1.77328 -4.250366 0.7698268
-Model cost at call 6 : 2000.127
+Negative log-likelihood at call 6: 2000.127
85.06375 -1.77328 -4.250366 0.7698268
85.06371 -1.773322 -4.250366 0.7698268
85.06371 -1.77328 -4.250408 0.7698268
85.06371 -1.77328 -4.250366 0.7697847
85.03542 -0.9608523 -4.11546 1.336361
-Model cost at call 11 : 32.97798
+Negative log-likelihood at call 11: 32.97798
85.03542 -0.9608523 -4.11546 1.336361
85.03542 -0.9608526 -4.11546 1.336361
85.03542 -0.9608523 -4.11546 1.336361
85.03542 -0.9608523 -4.11546 1.336361
85.03704 -0.256064 -4.273512 0.6447755
85.03285 -0.7822828 -4.127513 1.312494
-Model cost at call 17 : 5.348133
+Negative log-likelihood at call 17: 5.348133
85.03286 -0.7822828 -4.127513 1.312494
-Model cost at call 18 : 5.348132
+Negative log-likelihood at call 18: 5.348132
85.03285 -0.7822828 -4.127513 1.312494
-Model cost at call 19 : 5.348131
+Negative log-likelihood at call 19: 5.348131
85.03285 -0.7822828 -4.127513 1.312494
85.03285 -0.7822828 -4.127513 1.312494
-Model cost at call 21 : 5.348131
+Negative log-likelihood at call 21: 5.348131
85.02325 -0.74968 -4.059 1.14891
85.03127 -0.7909068 -4.114802 1.268157
-Model cost at call 23 : 4.704445
+Negative log-likelihood at call 23: 4.704445
85.03127 -0.7909068 -4.114802 1.268157
-Model cost at call 24 : 4.704444
+Negative log-likelihood at call 24: 4.704444
85.03127 -0.7909068 -4.114802 1.268157
85.03127 -0.7909068 -4.1148 1.268157
-Model cost at call 26 : 4.704433
+Negative log-likelihood at call 26: 4.704433
85.03127 -0.7909068 -4.114802 1.268158
85.03001 -0.7801506 -4.069435 1.262797
-Model cost at call 28 : 4.421625
+Negative log-likelihood at call 28: 4.421625
85.03001 -0.7801506 -4.069435 1.262797
85.03001 -0.7801507 -4.069435 1.262797
-Model cost at call 30 : 4.421624
+Negative log-likelihood at call 30: 4.421624
85.03001 -0.7801506 -4.069435 1.262797
85.03001 -0.7801506 -4.069435 1.262797
85.02878 -0.7900844 -4.023945 1.256918
85.02964 -0.7857352 -4.054587 1.260236
-Model cost at call 34 : 4.414346
+Negative log-likelihood at call 34: 4.414346
85.02964 -0.7857352 -4.054587 1.260236
85.02964 -0.7857351 -4.054587 1.260236
-Model cost at call 36 : 4.414346
+Negative log-likelihood at call 36: 4.414346
85.02964 -0.7857352 -4.054588 1.260236
85.02964 -0.7857352 -4.054587 1.260236
85.02812 -0.7778128 -4.042219 1.25389
-Model cost at call 39 : 4.372463
+Negative log-likelihood at call 39: 4.372463
85.02812 -0.7778128 -4.042219 1.25389
85.02812 -0.7778129 -4.042219 1.25389
-Model cost at call 41 : 4.372462
+Negative log-likelihood at call 41: 4.372462
85.02812 -0.7778128 -4.042219 1.25389
85.02812 -0.7778128 -4.042219 1.25389
85.02419 -0.7765144 -4.02942 1.245094
85.0263 -0.7778419 -4.036021 1.249634
-Model cost at call 45 : 4.369313
+Negative log-likelihood at call 45: 4.369313
85.0263 -0.7778419 -4.036021 1.249634
85.0263 -0.7778418 -4.036021 1.249634
-Model cost at call 47 : 4.369313
+Negative log-likelihood at call 47: 4.369313
85.0263 -0.7778419 -4.036022 1.249634
85.0263 -0.7778419 -4.036021 1.249634
-Model cost at call 49 : 4.369313
+Negative log-likelihood at call 49: 4.369313
85.02267 -0.7786811 -4.02967 1.252015
-Model cost at call 50 : 4.365062
+Negative log-likelihood at call 50: 4.365062
85.02268 -0.7786811 -4.02967 1.252015
85.02267 -0.7786812 -4.02967 1.252015
85.02267 -0.7786811 -4.02967 1.252015
-Model cost at call 53 : 4.365062
+Negative log-likelihood at call 53: 4.365062
85.02267 -0.7786811 -4.02967 1.252015
85.01633 -0.7763163 -4.027611 1.248897
-Model cost at call 55 : 4.364078
+Negative log-likelihood at call 55: 4.364078
85.01633 -0.7763163 -4.027611 1.248897
-Model cost at call 56 : 4.364078
+Negative log-likelihood at call 56: 4.364078
85.01633 -0.7763164 -4.027611 1.248897
-Model cost at call 57 : 4.364077
+Negative log-likelihood at call 57: 4.364077
85.01633 -0.7763163 -4.027611 1.248897
85.01633 -0.7763163 -4.027611 1.248897
85.00894 -0.7777917 -4.026307 1.24772
-Model cost at call 60 : 4.364052
+Negative log-likelihood at call 60: 4.364052
85.00894 -0.7777917 -4.026307 1.24772
-Model cost at call 61 : 4.364052
+Negative log-likelihood at call 61: 4.364052
85.00894 -0.7777917 -4.026307 1.24772
-Model cost at call 62 : 4.364052
+Negative log-likelihood at call 62: 4.364052
85.00894 -0.7777917 -4.026307 1.24772
85.00894 -0.7777917 -4.026307 1.24772
-Model cost at call 64 : 4.364052
+Negative log-likelihood at call 64: 4.364052
85.00518 -0.7773082 -4.026004 1.248453
-Model cost at call 65 : 4.362751
+Negative log-likelihood at call 65: 4.362751
85.00519 -0.7773082 -4.026004 1.248453
85.00518 -0.7773083 -4.026004 1.248453
-Model cost at call 67 : 4.362751
+Negative log-likelihood at call 67: 4.362751
85.00518 -0.7773082 -4.026005 1.248453
85.00518 -0.7773082 -4.026004 1.248453
85.00134 -0.7776046 -4.025878 1.248775
-Model cost at call 70 : 4.362721
+Negative log-likelihood at call 70: 4.362721
85.00135 -0.7776046 -4.025878 1.248775
-Model cost at call 71 : 4.362721
+Negative log-likelihood at call 71: 4.362721
85.00134 -0.7776046 -4.025878 1.248775
-Model cost at call 72 : 4.362721
+Negative log-likelihood at call 72: 4.362721
85.00134 -0.7776046 -4.025878 1.248775
85.00134 -0.7776046 -4.025878 1.248775
85.0032 -0.7774734 -4.0257 1.248643
-Model cost at call 75 : 4.362715
+Negative log-likelihood at call 75: 4.362715
85.0032 -0.7774734 -4.0257 1.248643
85.0032 -0.7774734 -4.0257 1.248643
-Model cost at call 77 : 4.362715
+Negative log-likelihood at call 77: 4.362715
85.0032 -0.7774735 -4.0257 1.248643
85.0032 -0.7774734 -4.0257 1.248643
85.0032 -0.7774734 -4.0257 1.248643
85.0032 -0.7774734 -4.0257 1.248643
85.00249 -0.7774909 -4.025911 1.248679
-Model cost at call 82 : 4.362715
+Negative log-likelihood at call 82: 4.362715
85.0025 -0.7774909 -4.025911 1.248679
-Model cost at call 83 : 4.362715
+Negative log-likelihood at call 83: 4.362715
85.00249 -0.7774909 -4.025911 1.248679
85.00249 -0.7774905 -4.025911 1.248679
85.00249 -0.7774914 -4.025911 1.248679
-Model cost at call 86 : 4.362715
+Negative log-likelihood at call 86: 4.362715
85.00249 -0.7774909 -4.025911 1.248679
85.00249 -0.7774909 -4.025911 1.248679
85.00249 -0.7774909 -4.025911 1.248679
85.00249 -0.7774909 -4.025911 1.248679
85.00274 -0.7774922 -4.025821 1.248672
-Model cost at call 91 : 4.362714
+Negative log-likelihood at call 91: 4.362714
85.00274 -0.7774922 -4.025821 1.248672
85.00274 -0.7774922 -4.025821 1.248672
-Model cost at call 93 : 4.362714
+Negative log-likelihood at call 93: 4.362714
85.00274 -0.7774921 -4.025821 1.248672
-Model cost at call 94 : 4.362714
+Negative log-likelihood at call 94: 4.362714
85.00274 -0.7774922 -4.025821 1.248672
85.00274 -0.7774922 -4.025821 1.248672
85.00274 -0.7774922 -4.025821 1.248672
85.00274 -0.7774922 -4.025821 1.248672
85.00274 -0.7774922 -4.025821 1.248672
85.00273 -0.7774912 -4.025817 1.24867
-Model cost at call 100 : 4.362714
+Negative log-likelihood at call 100: 4.362714
85.00275 -0.7774912 -4.025817 1.24867
85.00271 -0.7774912 -4.025817 1.24867
85.00273 -0.7774905 -4.025817 1.24867
@@ -152,7 +152,7 @@ Model cost at call 100 : 4.362714
85.00273 -0.7774912 -4.025817 1.248671
85.00273 -0.7774912 -4.025817 1.248669
85.00274 -0.7774913 -4.025819 1.248671
-Model cost at call 109 : 4.362714
+Negative log-likelihood at call 109: 4.362714
85.00276 -0.7774913 -4.025819 1.248671
85.00272 -0.7774913 -4.025819 1.248671
85.00274 -0.7774904 -4.025819 1.248671
@@ -162,109 +162,249 @@ Model cost at call 109 : 4.362714
85.00274 -0.7774913 -4.025819 1.248672
85.00274 -0.7774913 -4.025819 1.248669
85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-Model cost at call 123 : 4.362714
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-IRLS based on variance estimates according to the two component error model
-Initial variance components are:
-sigma_low rsd_high
- 1.08984 0.00000
-85.00274 -0.7774913 -4.025819 1.248671
-Model cost at call 129 : 3.673061
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-Model cost at call 132 : 3.673061
-85.00274 -0.7774913 -4.025819 1.248671
-85.00273 -0.7775309 -4.025818 1.24866
-85.00274 -0.7774953 -4.025819 1.24867
-85.00274 -0.7774917 -4.025819 1.248671
-85.00274 -0.7774914 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-Model cost at call 138 : 3.673061
-85.00277 -0.7774913 -4.025819 1.248671
-85.0027 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774744 -4.025819 1.248671
-85.00274 -0.7775083 -4.025819 1.248671
-85.00274 -0.7774913 -4.025779 1.248671
-85.00274 -0.7774913 -4.025858 1.248671
-85.00274 -0.7774913 -4.025819 1.248702
-85.00274 -0.7774913 -4.025819 1.248639
-85.00274 -0.7774913 -4.025819 1.248671
-Model cost at call 147 : 3.673061
-85.00276 -0.7774913 -4.025819 1.248671
-85.00271 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774906 -4.025819 1.248671
-85.00274 -0.7774921 -4.025819 1.248671
-85.00274 -0.7774913 -4.025812 1.248671
-85.00274 -0.7774913 -4.025825 1.248671
-85.00274 -0.7774913 -4.025819 1.248672
-85.00274 -0.7774913 -4.025819 1.248669
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-Model cost at call 159 : 3.673061
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-Iteration 1 yields variance estimates:
-sigma_low rsd_high
-0.7434091 0.0000000
-Sum of squared differences to last variance (component) estimates: 0.12
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-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00273 -0.7775366 -4.025821 1.248652
-85.00274 -0.7774959 -4.025819 1.248669
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-85.00274 -0.7774913 -4.025819 1.248671
-85.00279 -0.7774913 -4.025819 1.248671
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-85.00274 -0.7775206 -4.025819 1.248671
-85.00274 -0.7774913 -4.025761 1.248671
-85.00274 -0.7774913 -4.025876 1.248671
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-85.00274 -0.7774913 -4.025819 1.248627
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-85.00274 -0.7774913 -4.025819 1.248671
-85.00273 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774908 -4.025819 1.248671
-85.00274 -0.7774919 -4.025819 1.248671
-85.00274 -0.7774913 -4.025816 1.248671
-85.00274 -0.7774913 -4.025822 1.248671
-85.00274 -0.7774913 -4.025819 1.248672
-85.00274 -0.7774913 -4.025819 1.24867
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-85.00274 -0.7774913 -4.025819 1.248671
-Iteration 2 yields variance estimates:
-sigma_low rsd_high
-0.7434091 0.0000000
-Sum of squared differences to last variance (component) estimates: 2.9e-16
-Optimisation by method Port successfully terminated.
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+85.00274 0.4595574 0.01807191 0.8539454 0.696237
+85.00274 0.4595574 0.01762569 0.8539454 0.696237
+85.00274 0.4595574 0.0178488 0.93934 0.696237
+85.00274 0.4595574 0.0178488 0.7685509 0.696237
+85.00274 0.4595574 0.0178488 0.8966427 0.696237
+85.00274 0.4595574 0.0178488 0.8112482 0.696237
+85.00274 0.4595574 0.0178488 0.8752941 0.696237
+85.00274 0.4595574 0.0178488 0.8325968 0.696237
+85.00274 0.4595574 0.0178488 0.8646197 0.696237
+85.00274 0.4595574 0.0178488 0.8432711 0.696237
+85.00274 0.4595574 0.0178488 0.8539454 0.7658608
+85.00274 0.4595574 0.0178488 0.8539454 0.6266133
+85.00274 0.4595574 0.0178488 0.8539454 0.7310489
+85.00274 0.4595574 0.0178488 0.8539454 0.6614252
+85.00274 0.4595574 0.0178488 0.8539454 0.713643
+85.00274 0.4595574 0.0178488 0.8539454 0.6788311
+85.00274 0.4595574 0.0178488 0.8539454 0.70494
+85.00274 0.4595574 0.0178488 0.8539454 0.6875341
+93.50301 0.5055132 0.0178488 0.8539454 0.696237
+76.50246 0.4136017 0.0178488 0.8539454 0.696237
+89.25287 0.4825353 0.0178488 0.8539454 0.696237
+80.7526 0.4365796 0.0178488 0.8539454 0.696237
+87.12781 0.4710464 0.0178488 0.8539454 0.696237
+82.87767 0.4480685 0.0178488 0.8539454 0.696237
+86.06527 0.4653019 0.0178488 0.8539454 0.696237
+83.9402 0.453813 0.0178488 0.8539454 0.696237
+93.50301 0.4595574 0.01963368 0.8539454 0.696237
+76.50246 0.4595574 0.01606392 0.8539454 0.696237
+89.25287 0.4595574 0.01874124 0.8539454 0.696237
+80.7526 0.4595574 0.01695636 0.8539454 0.696237
+87.12781 0.4595574 0.01829502 0.8539454 0.696237
+82.87767 0.4595574 0.01740258 0.8539454 0.696237
+86.06527 0.4595574 0.01807191 0.8539454 0.696237
+83.9402 0.4595574 0.01762569 0.8539454 0.696237
+85.00274 0.5055132 0.01963368 0.8539454 0.696237
+85.00274 0.4136017 0.01606392 0.8539454 0.696237
+85.00274 0.4825353 0.01874124 0.8539454 0.696237
+85.00274 0.4365796 0.01695636 0.8539454 0.696237
+85.00274 0.4710464 0.01829502 0.8539454 0.696237
+85.00274 0.4480685 0.01740258 0.8539454 0.696237
+85.00274 0.4653019 0.01807191 0.8539454 0.696237
+85.00274 0.453813 0.01762569 0.8539454 0.696237
+93.50301 0.4595574 0.0178488 0.93934 0.696237
+76.50246 0.4595574 0.0178488 0.7685509 0.696237
+89.25287 0.4595574 0.0178488 0.8966427 0.696237
+80.7526 0.4595574 0.0178488 0.8112482 0.696237
+87.12781 0.4595574 0.0178488 0.8752941 0.696237
+82.87767 0.4595574 0.0178488 0.8325968 0.696237
+86.06527 0.4595574 0.0178488 0.8646197 0.696237
+83.9402 0.4595574 0.0178488 0.8432711 0.696237
+85.00274 0.5055132 0.0178488 0.93934 0.696237
+85.00274 0.4136017 0.0178488 0.7685509 0.696237
+85.00274 0.4825353 0.0178488 0.8966427 0.696237
+85.00274 0.4365796 0.0178488 0.8112482 0.696237
+85.00274 0.4710464 0.0178488 0.8752941 0.696237
+85.00274 0.4480685 0.0178488 0.8325968 0.696237
+85.00274 0.4653019 0.0178488 0.8646197 0.696237
+85.00274 0.453813 0.0178488 0.8432711 0.696237
+85.00274 0.4595574 0.01963368 0.93934 0.696237
+85.00274 0.4595574 0.01606392 0.7685509 0.696237
+85.00274 0.4595574 0.01874124 0.8966427 0.696237
+85.00274 0.4595574 0.01695636 0.8112482 0.696237
+85.00274 0.4595574 0.01829502 0.8752941 0.696237
+85.00274 0.4595574 0.01740258 0.8325968 0.696237
+85.00274 0.4595574 0.01807191 0.8646197 0.696237
+85.00274 0.4595574 0.01762569 0.8432711 0.696237
+93.50301 0.4595574 0.0178488 0.8539454 0.7658608
+76.50246 0.4595574 0.0178488 0.8539454 0.6266133
+89.25287 0.4595574 0.0178488 0.8539454 0.7310489
+80.7526 0.4595574 0.0178488 0.8539454 0.6614252
+87.12781 0.4595574 0.0178488 0.8539454 0.713643
+82.87767 0.4595574 0.0178488 0.8539454 0.6788311
+86.06527 0.4595574 0.0178488 0.8539454 0.70494
+83.9402 0.4595574 0.0178488 0.8539454 0.6875341
+85.00274 0.5055132 0.0178488 0.8539454 0.7658608
+85.00274 0.4136017 0.0178488 0.8539454 0.6266133
+85.00274 0.4825353 0.0178488 0.8539454 0.7310489
+85.00274 0.4365796 0.0178488 0.8539454 0.6614252
+85.00274 0.4710464 0.0178488 0.8539454 0.713643
+85.00274 0.4480685 0.0178488 0.8539454 0.6788311
+85.00274 0.4653019 0.0178488 0.8539454 0.70494
+85.00274 0.453813 0.0178488 0.8539454 0.6875341
+85.00274 0.4595574 0.01963368 0.8539454 0.7658608
+85.00274 0.4595574 0.01606392 0.8539454 0.6266133
+85.00274 0.4595574 0.01874124 0.8539454 0.7310489
+85.00274 0.4595574 0.01695636 0.8539454 0.6614252
+85.00274 0.4595574 0.01829502 0.8539454 0.713643
+85.00274 0.4595574 0.01740258 0.8539454 0.6788311
+85.00274 0.4595574 0.01807191 0.8539454 0.70494
+85.00274 0.4595574 0.01762569 0.8539454 0.6875341
+85.00274 0.4595574 0.0178488 0.93934 0.7658608
+85.00274 0.4595574 0.0178488 0.7685509 0.6266133
+85.00274 0.4595574 0.0178488 0.8966427 0.7310489
+85.00274 0.4595574 0.0178488 0.8112482 0.6614252
+85.00274 0.4595574 0.0178488 0.8752941 0.713643
+85.00274 0.4595574 0.0178488 0.8325968 0.6788311
+85.00274 0.4595574 0.0178488 0.8646197 0.70494
+85.00274 0.4595574 0.0178488 0.8432711 0.6875341
+Optimisation successfully terminated.
diff --git a/tests/testthat/FOCUS_2006_D.csf b/tests/testthat/FOCUS_2006_D.csf
index c14aab4d..84500b54 100644
--- a/tests/testthat/FOCUS_2006_D.csf
+++ b/tests/testthat/FOCUS_2006_D.csf
@@ -5,7 +5,7 @@ Description:
MeasurementUnits: % AR
TimeUnits: days
Comments: Created using mkin::CAKE_export
-Date: 2019-03-04
+Date: 2019-04-10
Optimiser: IRLS
[Data]
diff --git a/tests/testthat/NAFTA_SOP_Appendix_B.txt b/tests/testthat/NAFTA_SOP_Appendix_B.txt
index 26a340c5..9c072d58 100644
--- a/tests/testthat/NAFTA_SOP_Appendix_B.txt
+++ b/tests/testthat/NAFTA_SOP_Appendix_B.txt
@@ -8,21 +8,24 @@ Critical sum of squares for checking the SFO model:
Parameters:
$SFO
Estimate Pr(>t) Lower Upper
-parent_0 51.243 1.18e-10 45.404 57.082
-k_parent_sink 0.253 1.61e-06 0.194 0.331
+parent_0 51.243 2.12e-10 45.724 56.762
+k_parent_sink 0.253 2.95e-06 0.193 0.332
+sigma 3.529 1.28e-04 2.061 4.997
$IORE
Estimate Pr(>t) Lower Upper
-parent_0 51.71053 8.52e-15 4.95e+01 53.90735
-k__iore_parent_sink 0.00135 6.84e-02 3.42e-04 0.00531
-N_parent 2.66147 3.98e-08 2.19e+00 3.13193
+parent_0 51.71053 2.60e-14 4.97e+01 53.68122
+k__iore_parent_sink 0.00135 5.21e-02 3.88e-04 0.00469
+N_parent 2.66147 3.67e-08 2.23e+00 3.08855
+sigma 1.25124 1.76e-04 7.24e-01 1.77811
$DFOP
Estimate Pr(>t) Lower Upper
-parent_0 51.7055 3.46e-14 49.67793 53.7330
-k1 0.4157 1.00e-06 0.33077 0.5224
-k2 0.0127 1.39e-03 0.00723 0.0224
-g 0.8338 5.72e-12 0.77182 0.8815
+parent_0 51.7055 8.99e-14 49.96593 53.4450
+k1 0.4157 5.65e-07 0.34129 0.5063
+k2 0.0127 7.78e-04 0.00768 0.0211
+g 0.8338 1.09e-11 0.78030 0.8763
+sigma 1.0880 2.50e-04 0.62286 1.5531
DTx values:
diff --git a/tests/testthat/NAFTA_SOP_Appendix_D.txt b/tests/testthat/NAFTA_SOP_Appendix_D.txt
index 1e846a16..ad650a5f 100644
--- a/tests/testthat/NAFTA_SOP_Appendix_D.txt
+++ b/tests/testthat/NAFTA_SOP_Appendix_D.txt
@@ -7,22 +7,25 @@ Critical sum of squares for checking the SFO model:
Parameters:
$SFO
- Estimate Pr(>t) Lower Upper
-parent_0 83.7558 8.08e-15 76.92822 90.58328
-k_parent_sink 0.0017 7.45e-05 0.00111 0.00262
+ Estimate Pr(>t) Lower Upper
+parent_0 83.7558 1.80e-14 77.18268 90.3288
+k_parent_sink 0.0017 7.43e-05 0.00112 0.0026
+sigma 8.7518 1.22e-05 5.64278 11.8608
$IORE
Estimate Pr(>t) Lower Upper
-parent_0 9.69e+01 NA 8.75e+01 1.06e+02
-k__iore_parent_sink 8.40e-14 NA 1.09e-19 6.47e-08
-N_parent 6.68e+00 NA 3.54e+00 9.83e+00
+parent_0 9.69e+01 NA 8.88e+01 1.05e+02
+k__iore_parent_sink 8.40e-14 NA 1.79e-18 3.94e-09
+N_parent 6.68e+00 NA 4.19e+00 9.17e+00
+sigma 5.85e+00 NA 3.76e+00 7.94e+00
$DFOP
Estimate Pr(>t) Lower Upper
-parent_0 9.76e+01 4.44e-13 8.88e+01 1.06e+02
-k1 4.24e-02 3.55e-02 1.41e-02 1.27e-01
-k2 8.24e-04 2.06e-02 3.17e-04 2.14e-03
-g 2.88e-01 1.31e-04 1.78e-01 4.30e-01
+parent_0 9.76e+01 1.94e-13 9.02e+01 1.05e+02
+k1 4.24e-02 5.92e-03 2.03e-02 8.88e-02
+k2 8.24e-04 6.48e-03 3.89e-04 1.75e-03
+g 2.88e-01 2.47e-05 1.95e-01 4.03e-01
+sigma 5.36e+00 2.22e-05 3.43e+00 7.30e+00
DTx values:
@@ -32,4 +35,4 @@ IORE 541 5190000 1560000
DFOP 429 2380 841
Representative half-life:
-[1] 841.4096
+[1] 841.4094
diff --git a/tests/testthat/summary_DFOP_FOCUS_C.txt b/tests/testthat/summary_DFOP_FOCUS_C.txt
index 33d55ebc..1d669d43 100644
--- a/tests/testthat/summary_DFOP_FOCUS_C.txt
+++ b/tests/testthat/summary_DFOP_FOCUS_C.txt
@@ -10,16 +10,18 @@ d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
Model predictions using solution type analytical
-Fitted with method Port using test 0 model solutions performed in test time 0 s
+Fitted with method using test 0 model solutions performed in test time 0 s
-Weighting: none
+Error model:
+NULL
Starting values for parameters to be optimised:
- value type
-parent_0 85.10 state
-k1 0.10 deparm
-k2 0.01 deparm
-g 0.50 deparm
+ value type
+parent_0 85.100000 state
+k1 0.100000 deparm
+k2 0.010000 deparm
+g 0.500000 deparm
+sigma 0.696237 error
Starting values for the transformed parameters actually optimised:
value lower upper
@@ -27,35 +29,37 @@ parent_0 85.100000 -Inf Inf
log_k1 -2.302585 -Inf Inf
log_k2 -4.605170 -Inf Inf
g_ilr 0.000000 -Inf Inf
+sigma 0.696237 0 Inf
Fixed parameter values:
None
Optimised, transformed parameters with symmetric confidence intervals:
Estimate Std. Error Lower Upper
-parent_0 85.0000 0.89070 82.7100 87.2900
-log_k1 -0.7775 0.04430 -0.8914 -0.6636
-log_k2 -4.0260 0.17030 -4.4640 -3.5880
-g_ilr 1.2490 0.07619 1.0530 1.4450
+parent_0 85.0000 0.66620 83.1500 86.8500
+log_k1 -0.7775 0.03380 -0.8713 -0.6836
+log_k2 -4.0260 0.13100 -4.3890 -3.6620
+g_ilr 1.2490 0.05811 1.0870 1.4100
+sigma 0.6962 0.16410 0.2406 1.1520
Parameter correlation:
- parent_0 log_k1 log_k2 g_ilr
-parent_0 1.00000 0.4338 0.07924 -0.01897
-log_k1 0.43380 1.0000 0.46567 -0.66010
-log_k2 0.07924 0.4657 1.00000 -0.74183
-g_ilr -0.01897 -0.6601 -0.74183 1.00000
-
-Residual standard error: 0.9341 on 5 degrees of freedom
+ parent_0 log_k1 log_k2 g_ilr sigma
+parent_0 1.000e+00 4.393e-01 8.805e-02 -3.176e-02 5.405e-07
+log_k1 4.393e-01 1.000e+00 4.821e-01 -6.716e-01 4.395e-07
+log_k2 8.805e-02 4.821e-01 1.000e+00 -7.532e-01 -1.151e-07
+g_ilr -3.176e-02 -6.716e-01 -7.532e-01 1.000e+00 -2.142e-08
+sigma 5.405e-07 4.395e-07 -1.151e-07 -2.142e-08 1.000e+00
Backtransformed parameters:
Confidence intervals for internally transformed parameters are asymmetric.
t-test (unrealistically) based on the assumption of normal distribution
for estimators of untransformed parameters.
Estimate t value Pr(>t) Lower Upper
-parent_0 85.00000 95.440 1.197e-09 82.71000 87.29000
-k1 0.45960 22.570 1.586e-06 0.41010 0.51500
-k2 0.01785 5.873 1.016e-03 0.01152 0.02765
-g 0.85390 63.540 9.135e-09 0.81590 0.88520
+parent_0 85.00000 127.600 1.131e-08 83.15000 86.85000
+k1 0.45960 29.580 3.887e-06 0.41840 0.50480
+k2 0.01785 7.636 7.901e-04 0.01241 0.02568
+g 0.85390 83.310 6.221e-08 0.82310 0.88020
+sigma 0.69620 4.243 6.618e-03 0.24060 1.15200
Chi2 error levels in percent:
err.min n.optim df
diff --git a/tests/testthat/test_FOCUS_D_UBA_expertise.R b/tests/testthat/test_FOCUS_D_UBA_expertise.R
index 42c4fcfb..3a49078c 100644
--- a/tests/testthat/test_FOCUS_D_UBA_expertise.R
+++ b/tests/testthat/test_FOCUS_D_UBA_expertise.R
@@ -27,20 +27,18 @@ SFO_SFO.ff <- mkinmod(parent = list(type = "SFO", to = "m1"),
test_that("Fits without formation fractions are correct for FOCUS D", {
- fit.default <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
+ fit.default <- expect_warning(mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE), "value of zero")
expect_equal(round(as.numeric(endpoints(fit.default)$distimes["parent", ]), 2),
c(7.02, 23.33))
expect_equal(round(as.numeric(endpoints(fit.default)$distimes["m1", ]), 1),
c(131.8, 437.7))
- expect_equal(signif(summary(fit.default)$bpar[, "t value"], 5),
- c(parent_0 = 61.720, k_parent_sink = 12.777, k_parent_m1 = 24.248, k_m1_sink = 7.3486))
})
test_that("Fits with formation fractions are correct for FOCUS D", {
skip_on_cran()
- fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
+ fit.ff <- expect_warning(mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE), "value of zero")
expect_equivalent(round(fit.ff$bparms.optim, c(2, 4, 4, 4)),
c(99.60, 0.0987, 0.0053, 0.5145))
@@ -88,6 +86,7 @@ test_that("The t-value for fits using internal transformations corresponds with
synthetic_data_for_UBA_2014[[12]]$data,
quiet = TRUE)
+ skip("Hessian matrices and df calculations differ from those in FME")
# Note that the k1 and k2 are exchanged in the untransformed fit evaluated with FME for this test
expect_equal(signif(summary(fit_DFOP_par_c_2)$bpar[1:7, "t value"], 5),
c(parent_0 = 80.054, k_M1_sink = 12.291, k_M2_sink = 10.588,
diff --git a/tests/testthat/test_FOCUS_chi2_error_level.R b/tests/testthat/test_FOCUS_chi2_error_level.R
index 1f1e2a06..69a8c2ad 100644
--- a/tests/testthat/test_FOCUS_chi2_error_level.R
+++ b/tests/testthat/test_FOCUS_chi2_error_level.R
@@ -26,7 +26,8 @@ SFO_SFO.ff <- mkinmod(parent = list(type = "SFO", to = "m1"),
test_that("Chi2 error levels for FOCUS D are as in mkin 0.9-33", {
- fit <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
+ fit <- expect_warning(mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE),
+ "Observations with value of zero")
errmin.FOCUS_2006_D_rounded = data.frame(
err.min = c(0.0640, 0.0646, 0.0469),
diff --git a/tests/testthat/test_error_models.R b/tests/testthat/test_error_models.R
index bda8ca7f..5a7aa4e8 100644
--- a/tests/testthat/test_error_models.R
+++ b/tests/testthat/test_error_models.R
@@ -1,4 +1,4 @@
-# Copyright (C) 2018 Johannes Ranke
+# Copyright (C) 2018,2019 Johannes Ranke
# Contact: jranke@uni-bremen.de
# This file is part of the R package mkin
@@ -70,13 +70,6 @@ test_that("Error model 'tc' works", {
expect_equivalent(parms_3, c(102.1, 0.7393, 0.2992, 0.0202, 0.7687, 0.7229))
})
-test_that("Error model 'obs_tc' works", {
- skip_on_cran()
- fit_obs_tc_1 <- expect_warning(mkinfit(m_synth_SFO_lin, SFO_lin_a, error_model = "obs_tc", quiet = TRUE), "NaN")
- # Here the error model is overparameterised
- expect_warning(summary(fit_obs_tc_1), "singular system")
-})
-
test_that("Reweighting method 'tc' produces reasonable variance estimates", {
# I need to make the tc method more robust against that
@@ -148,7 +141,7 @@ test_that("Reweighting method 'tc' produces reasonable variance estimates", {
d_met_2_15 <- add_err(d_synth_DFOP_lin,
sdfunc = function(x) sigma_twocomp(x, 0.5, 0.07),
- n = 15, reps = 100, digits = 5, LOD = -Inf, seed = 123456)
+ n = 15, reps = 100, digits = 5, LOD = 0.01, seed = 123456)
# For a single fit, we get a relative error of less than 10% in the error
# model components
@@ -165,14 +158,14 @@ test_that("Reweighting method 'tc' produces reasonable variance estimates", {
parms_met_2_15_tc_e4 <- apply(sapply(f_met_2_15_tc_e4, function(x) x$bparms.optim), 1, mean)
parm_errors_met_2_15_tc_e4 <- (parms_met_2_15_tc_e4[names(parms_DFOP_lin_optim)] -
parms_DFOP_lin_optim) / parms_DFOP_lin_optim
- expect_true(all(abs(parm_errors_met_2_15_tc_e4) < 0.01))
+ expect_true(all(abs(parm_errors_met_2_15_tc_e4) < 0.015))
tcf_met_2_15_tc <- apply(sapply(f_met_2_15_tc_e4, function(x) x$errparms), 1, mean, na.rm = TRUE)
tcf_met_2_15_tc_error_model_errors <- (tcf_met_2_15_tc - c(0.5, 0.07)) /
c(0.5, 0.07)
- # Here we get a precision < 15% for retrieving the original error model components
+ # Here we get a precision < 10% for retrieving the original error model components
# from 15 datasets
- expect_true(all(abs(tcf_met_2_15_tc_error_model_errors) < 0.15))
+ expect_true(all(abs(tcf_met_2_15_tc_error_model_errors) < 0.10))
})
diff --git a/tests/testthat/test_from_max_mean.R b/tests/testthat/test_from_max_mean.R
index 7529c5f2..c4d6bfe4 100644
--- a/tests/testthat/test_from_max_mean.R
+++ b/tests/testthat/test_from_max_mean.R
@@ -1,4 +1,4 @@
-# Copyright (C) 2018 Johannes Ranke
+# Copyright (C) 2018,2019 Johannes Ranke
# Contact: jranke@uni-bremen.de
# This file is part of the R package mkin
@@ -21,15 +21,19 @@ context("Test fitting the decline of metabolites from their maximum")
test_that("Fitting from maximum mean value works", {
SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"),
m1 = mkinsub("SFO"))
- expect_error(mkinfit(SFO_SFO, FOCUS_2006_D, from_max_mean = TRUE))
+ expect_warning(
+ expect_error(mkinfit(SFO_SFO, FOCUS_2006_D, from_max_mean = TRUE),
+ "only implemented for models with a single observed variable"),
+ "Observations with value of zero were removed")
# We can either explicitly create a model for m1, or subset the data
SFO_m1 <- mkinmod(m1 = mkinsub("SFO"))
- f.1 <- mkinfit(SFO_m1, FOCUS_2006_D, from_max_mean = TRUE, quiet = TRUE)
+ f.1 <- expect_warning(mkinfit(SFO_m1, FOCUS_2006_D, from_max_mean = TRUE, quiet = TRUE))
expect_equivalent(endpoints(f.1)$distimes["m1", ], c(170.8, 567.5),
scale = 1, tolerance = 0.1)
- f.2 <- mkinfit("SFO", subset(FOCUS_2006_D, name == "m1"), from_max_mean = TRUE, quiet = TRUE)
+ f.2 <- expect_warning(mkinfit("SFO", subset(FOCUS_2006_D, name == "m1"),
+ from_max_mean = TRUE, quiet = TRUE))
expect_equivalent(endpoints(f.2)$distimes["m1", ], c(170.8, 567.5),
scale = 1, tolerance = 0.1)
})
diff --git a/tests/testthat/test_mkinfit_errors.R b/tests/testthat/test_mkinfit_errors.R
index f1b4618c..fa029d93 100644
--- a/tests/testthat/test_mkinfit_errors.R
+++ b/tests/testthat/test_mkinfit_errors.R
@@ -30,6 +30,9 @@ test_that("mkinfit stops to prevent and/or explain user errors", {
expect_error(mkinfit("foo", FOCUS_2006_A))
expect_error(mkinfit(3, FOCUS_2006_A))
+ # We remove zero observations from FOCUS_2006_D beforehand in
+ # order to avoid another expect_warning in the code
+ FOCUS_2006_D <- subset(FOCUS_2006_D, value != 0)
# We get a warning if we use transform_fractions = FALSE with formation fractions
# and an error if any pathway to sink is turned off as well
expect_warning(
@@ -50,26 +53,16 @@ test_that("mkinfit stops to prevent and/or explain user errors", {
expect_error(mkinfit(SFO_SFO.ff, FOCUS_2006_D, solution_type = "analytical"), "not implemented")
expect_error(mkinfit("FOMC", FOCUS_2006_A, solution_type = "eigen"), "coefficient matrix not present")
-
- # We suppress a message stemming from the interrupted call to system.time()
- expect_error(suppressMessages(mkinfit("SFO", FOCUS_2006_A, reweight.method =
- "foo", quiet = TRUE), "implemented"))
-
})
test_that("mkinfit stops early when a low maximum number of iterations is specified", {
- expect_warning(mkinfit("SFO", FOCUS_2006_A, maxit.modFit = 1, quiet = TRUE))
- expect_warning(mkinfit("SFO", FOCUS_2006_A, maxit.modFit = 1, quiet = TRUE, method.modFit = "Marq"))
-})
-
-test_that("mkinfit warns if the user chooses the SANN method", {
- expect_warning(mkinfit("SFO", FOCUS_2006_A, method.modFit = "SANN", maxit.modFit = 10, quiet = TRUE))
- skip("The SANN algorithm takes very long with the default maximum number of iterations of 10000")
- expect_warning(mkinfit("SFO", FOCUS_2006_A, method.modFit = "SANN"))
+ expect_warning(mkinfit("SFO", FOCUS_2006_A, control = list(iter.max = 1), quiet = TRUE),
+ "iteration limit reached without convergence")
})
test_that("mkinfit warns if a specified initial parameter value is not in the model", {
- expect_warning(mkinfit("SFO", FOCUS_2006_A, parms.ini = c(k_xy = 0.1), quiet = TRUE))
+ expect_warning(mkinfit("SFO", FOCUS_2006_A, parms.ini = c(k_xy = 0.1), quiet = TRUE),
+ "not used in the model")
})
test_that("We get reproducible output if quiet = FALSE", {
@@ -83,5 +76,6 @@ test_that("We get reproducible output if quiet = FALSE", {
test_that("We get warnings in case of overparameterisation", {
skip_on_cran() # On winbuilder the following fit does not give a warning
expect_warning(f <- mkinfit("FOMC", FOCUS_2006_A, quiet = TRUE), "not converge")
- s2 <- expect_warning(summary(mkinfit("DFOP", FOCUS_2006_A, quiet = TRUE)), "singular system")
+ # We do get Hessians and the related output after the switch to using numDeriv::hessian()
+ #s2 <- expect_warning(summary(mkinfit("DFOP", FOCUS_2006_A, quiet = TRUE)), "singular system")
})
diff --git a/tests/testthat/test_nafta.R b/tests/testthat/test_nafta.R
index 9528200d..096287aa 100644
--- a/tests/testthat/test_nafta.R
+++ b/tests/testthat/test_nafta.R
@@ -43,8 +43,8 @@ test_that("Test data from Appendix B are correctly evaluated", {
})
test_that("Test data from Appendix D are correctly evaluated", {
- expect_warning(res <- nafta(NAFTA_SOP_Appendix_D, "MRID 555555",
- cores = 1, quiet = TRUE))
+ res <- nafta(NAFTA_SOP_Appendix_D, "MRID 555555",
+ cores = 1, quiet = TRUE)
# From Figure D.1
dtx_sop <- matrix(c(407, 541, 429, 1352, 5192066, 2383), nrow = 3, ncol = 2)
diff --git a/tests/testthat/test_plots_summary_twa.R b/tests/testthat/test_plots_summary_twa.R
index 201faa73..cf5715fa 100644
--- a/tests/testthat/test_plots_summary_twa.R
+++ b/tests/testthat/test_plots_summary_twa.R
@@ -79,8 +79,8 @@ test_that("Plotting mmkin objects is reproducible", {
context("AIC calculation")
test_that("The AIC is reproducible", {
- expect_equivalent(AIC(fits[["SFO", "FOCUS_C"]]), 59.8, scale = 1, tolerance = 0.1)
+ expect_equivalent(AIC(fits[["SFO", "FOCUS_C"]]), 59.3, scale = 1, tolerance = 0.1)
expect_equivalent(AIC(fits[, "FOCUS_C"]),
- data.frame(df = c(3, 4, 5, 5), AIC = c(59.8, 44.7, 29.1, 39.3)),
+ data.frame(df = c(3, 4, 5, 5), AIC = c(59.3, 44.7, 29.0, 39.2)),
scale = 1, tolerance = 0.1)
})
diff --git a/tests/testthat/test_schaefer07_complex_case.R b/tests/testthat/test_schaefer07_complex_case.R
index 844dd88f..66ebc03b 100644
--- a/tests/testthat/test_schaefer07_complex_case.R
+++ b/tests/testthat/test_schaefer07_complex_case.R
@@ -57,10 +57,11 @@ test_that("Complex test case from Schaefer (2007) can be reproduced (10% toleran
r$mkin.deviation <- abs(round(100 * ((r$mkin - r$means)/r$means), digits=1))
expect_equal(r$mkin.deviation < 10, rep(TRUE, 14))
- # If we use optimisation algorithm 'Marq' we get a local minimum with a
- # sum of squared residuals of 273.3707
- # When using 'Marq', we need to give a good starting estimate e.g. for k_A2 in
+ # In previous versions of mkinfit, if we used optimisation algorithm 'Marq'
+ # we got a local minimum with a sum of squared residuals of 273.3707
+ # When using 'Marq', we needed to give a good starting estimate e.g. for k_A2 in
# order to get the optimum with sum of squared residuals 240.5686
- expect_equal(round(fit.default$ssr, 4), 240.5686)
+ ssr <- sum(fit.default$data$residual^2)
+ expect_equal(round(ssr, 4), 240.5686)
})

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