Warn if standardized residuals are unlikely normal

This revealed a bug in the data returned in mkinfit$data in the case
of the d_3 algorithm, which also affected the residual plot - the
data from the direct fitting was not returned even if this was
the better method.

8 files changed, 51 insertions, 32 deletions

diff --git a/tests/testthat/FOCUS_2006_D.csf b/tests/testthat/FOCUS_2006_D.csf
index f845cc1d..7c8340cd 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: 2020-05-28
+Date: 2020-05-29
 Optimiser: IRLS
 
 [Data]
diff --git a/tests/testthat/setup_script.R b/tests/testthat/setup_script.R
index def52697..8d8ba3e9 100644
--- a/tests/testthat/setup_script.R
+++ b/tests/testthat/setup_script.R
@@ -57,18 +57,26 @@ DFOP_SFO <- mkinmod(parent = mkinsub("DFOP", to = "m1"),
 # Avoid warning when fitting a dataset where zero value is removed
 FOCUS_D <- subset(FOCUS_2006_D, value != 0)
 
+# We do not want warnings about non-normality of residuals here
+suppressWarnings(
 f_sfo_sfo_desolve <- mkinfit(SFO_SFO, FOCUS_D,
   solution_type = "deSolve", quiet = TRUE)
+)
+suppressWarnings(
 f_sfo_sfo_eigen <- mkinfit(SFO_SFO, FOCUS_D,
   solution_type = "eigen", quiet = TRUE)
-
+)
+suppressWarnings(
 f_sfo_sfo.ff <- mkinfit(SFO_SFO.ff, FOCUS_D,
   quiet = TRUE)
+)
 
 SFO_lin_a <- synthetic_data_for_UBA_2014[[1]]$data
 DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data
 
-f_2_mkin <- mkinfit("DFOP", DFOP_par_c, quiet = TRUE)
+# We also suppress the warning about non-normality of residuals here, the data
+# were generated with a different error model, so no wonder!
+f_2_mkin <- suppressWarnings(mkinfit("DFOP", DFOP_par_c, quiet = TRUE))
 f_2_nls <- nls(value ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = subset(DFOP_par_c, name == "parent"))
 f_2_anova <- lm(value ~ as.factor(time), data = subset(DFOP_par_c, name == "parent"))
 
@@ -86,9 +94,9 @@ m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
 
 fit_nw_1 <- mkinfit(m_synth_SFO_lin, SFO_lin_a, quiet = TRUE)
 
-# We know direct optimization is OK and direct needs 4 sec versus 5.5 for threestep and 6 for IRLS
+# We know direct optimization is OK and direct is faster than the default d_3
 fit_obs_1 <- mkinfit(m_synth_SFO_lin, SFO_lin_a, error_model = "obs", quiet = TRUE,
   error_model_algorithm = "direct")
-# We know threestep is OK, and threestep (and IRLS) need 4.8 se versus 5.6 for direct
+# We know threestep is OK, and threestep (and IRLS) is faster here
 fit_tc_1 <- mkinfit(m_synth_SFO_lin, SFO_lin_a, error_model = "tc", quiet = TRUE,
   error_model_algorithm = "threestep")
diff --git a/tests/testthat/test_FOCUS_D_UBA_expertise.R b/tests/testthat/test_FOCUS_D_UBA_expertise.R
index be2806de..101c8e15 100644
--- a/tests/testthat/test_FOCUS_D_UBA_expertise.R
+++ b/tests/testthat/test_FOCUS_D_UBA_expertise.R
@@ -2,11 +2,10 @@ context("Results for FOCUS D established in expertise for UBA (Ranke 2014)")
 
 # Results are from p. 40
 
-# Avoid warnings due to the zero value in the data for m1 at time zero
-FOCUS_D <- subset(FOCUS_2006_D, value != 0)
-
 test_that("Fits without formation fractions are correct for FOCUS D", {
-  fit.noff <- mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE)
+  expect_warning(
+    fit.noff <- mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE),
+    "p-value.*Shapiro-Wilk")
 
   expect_equal(round(as.numeric(endpoints(fit.noff)$distimes["parent", ]), 2),
                c(7.02, 23.33))
@@ -16,8 +15,7 @@ test_that("Fits without formation fractions are correct for FOCUS D", {
 })
 
 test_that("Fits with formation fractions are correct for FOCUS D", {
-  skip_on_cran()
-  fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_D, quiet = TRUE)
+  fit.ff <- f_sfo_sfo.ff
   expect_equivalent(round(fit.ff$bparms.optim, c(2, 4, 4, 4)),
                     c(99.60, 0.0987, 0.0053, 0.5145))
 
diff --git a/tests/testthat/test_SFORB.R b/tests/testthat/test_SFORB.R
index 4fb736ec..91c8f2fb 100644
--- a/tests/testthat/test_SFORB.R
+++ b/tests/testthat/test_SFORB.R
@@ -1,5 +1,8 @@
 context("Fitting the SFORB model")
 
+# We do not want the warnings due to non-normality of residuals here
+warn_option <- options(warn=-1)
+
 test_that("Fitting the SFORB model is equivalent to fitting DFOP", {
   f_sforb <- mkinfit("SFORB", FOCUS_2006_C, quiet = TRUE)
   f_dfop <- mkinfit("DFOP", FOCUS_2006_C, quiet = TRUE)
@@ -32,3 +35,5 @@ test_that("Fitting the SFORB model is equivalent to fitting DFOP", {
   expect_equivalent(endpoints(f_sforb_sfo_eigen)$distimes, endpoints(f_dfop_sfo)$distimes,
     tolerance = 1e-6)
 })
+
+options(warn = warn_option$warn)
diff --git a/tests/testthat/test_analytical.R b/tests/testthat/test_analytical.R
index a34fa2cd..66fb1ace 100644
--- a/tests/testthat/test_analytical.R
+++ b/tests/testthat/test_analytical.R
@@ -1,5 +1,8 @@
 context("Analytical solutions for coupled models")
 
+# We do not want the warnings due to non-normality of residuals here
+warn_option <- options(warn=-1)
+
 test_that("The analytical solutions for SFO-SFO are correct", {
   # No sink, no formation fractions
   SFO_SFO_nosink <- mkinmod(
@@ -58,3 +61,5 @@ test_that("The analytical solution for DFOP-SFO are correct", {
     tolerance = 5e-6
   )
 })
+
+options(warn = warn_option$warn)
diff --git a/tests/testthat/test_error_models.R b/tests/testthat/test_error_models.R
index 2dfb2e37..169001f1 100644
--- a/tests/testthat/test_error_models.R
+++ b/tests/testthat/test_error_models.R
@@ -15,36 +15,37 @@ test_that("Error model 'tc' works", {
 test_that("The different error model fitting methods work for parent fits", {
   skip_on_cran()
 
-  f_9_OLS <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
-                     quiet = TRUE)
+  test_9 <- experimental_data_for_UBA_2019[[9]]$data
+
+  f_9_OLS <- mkinfit("SFO", test_9, quiet = TRUE)
   expect_equivalent(round(AIC(f_9_OLS), 2), 137.43)
   f_9_parms_const <- parms(f_9_OLS)
 
-  f_9_direct <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+  f_9_direct <- mkinfit("SFO", test_9,
     error_model = "tc", error_model_algorithm = "direct", quiet = TRUE)
   expect_equivalent(round(AIC(f_9_direct), 2), 134.94)
   f_9_parms_tc_direct <- parms(f_9_direct)
 
-  f_9_twostep <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+  f_9_twostep <- mkinfit("SFO", test_9,
     error_model = "tc", error_model_algorithm = "twostep", quiet = TRUE)
   expect_equivalent(parms(f_9_twostep), f_9_parms_tc_direct, tolerance = 1e-5)
 
-  f_9_threestep <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+  f_9_threestep <- mkinfit("SFO", test_9,
     error_model = "tc", error_model_algorithm = "threestep", quiet = TRUE)
   expect_equivalent(round(AIC(f_9_threestep), 2), 139.43)
   expect_equivalent(parms(f_9_threestep)[1:3], f_9_parms_const)
 
-  f_9_fourstep <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+  f_9_fourstep <- mkinfit("SFO", test_9,
     error_model = "tc", error_model_algorithm = "fourstep", quiet = TRUE)
   expect_equivalent(round(AIC(f_9_fourstep), 2), 139.43)
   expect_equivalent(parms(f_9_fourstep)[1:3], f_9_parms_const)
 
-  f_9_IRLS <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+  f_9_IRLS <- mkinfit("SFO", test_9,
     error_model = "tc", error_model_algorithm = "IRLS", quiet = TRUE)
   expect_equivalent(round(AIC(f_9_IRLS), 2), 139.43)
   expect_equivalent(parms(f_9_IRLS)[1:3], f_9_parms_const)
 
-  f_9_d_3 <- mkinfit("SFO", experimental_data_for_UBA_2019[[9]]$data,
+  f_9_d_3 <- mkinfit("SFO", test_9,
     error_model = "tc", error_model_algorithm = "d_3", quiet = TRUE)
   expect_equivalent(round(AIC(f_9_d_3), 2), 134.94)
   expect_equivalent(parms(f_9_d_3), f_9_parms_tc_direct)
diff --git a/tests/testthat/test_nafta.R b/tests/testthat/test_nafta.R
index 2cc25f82..595db999 100644
--- a/tests/testthat/test_nafta.R
+++ b/tests/testthat/test_nafta.R
@@ -28,8 +28,11 @@ test_that("Test data from Appendix B are correctly evaluated", {
 })
 
 test_that("Test data from Appendix D are correctly evaluated", {
+  # We are not interested in the warnings about non-normal residuals here
+  suppressWarnings(
   res <- nafta(NAFTA_SOP_Appendix_D, "MRID 555555", 
-                              cores = 1, quiet = TRUE)
+    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_synthetic_data_for_UBA_2014.R b/tests/testthat/test_synthetic_data_for_UBA_2014.R
index 4bff1b5a..989f963a 100644
--- a/tests/testthat/test_synthetic_data_for_UBA_2014.R
+++ b/tests/testthat/test_synthetic_data_for_UBA_2014.R
@@ -7,8 +7,8 @@ test_that("Results are correct for SFO_lin_a", {
                              M1 = mkinsub("SFO", "M2"),
                              M2 = mkinsub("SFO"),
                              use_of_ff = "max", quiet = TRUE)
-  fit_SFO_lin_a <- mkinfit(m_synth_SFO_lin, 
-                           synthetic_data_for_UBA_2014[[1]]$data, 
+  fit_SFO_lin_a <- mkinfit(m_synth_SFO_lin,
+                           synthetic_data_for_UBA_2014[[1]]$data,
                            quiet = TRUE)
   # Results for SFO_lin_a from p. 48
 
@@ -21,19 +21,18 @@ test_that("Results are correct for SFO_lin_a", {
 # Results for DFOP_par_c from p. 54
 
 test_that("Results are correct for DFOP_par_c", {
-  skip_on_cran()          
-  m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
-                             M1 = mkinsub("SFO"),
-                             M2 = mkinsub("SFO"),
-                             use_of_ff = "max", quiet = TRUE)
-
+  skip_on_cran()
 
-  fit_DFOP_par_c <- mkinfit(m_synth_DFOP_par, 
-                            synthetic_data_for_UBA_2014[[12]]$data,
-                            quiet = TRUE)
+  # Supress warning about non-normal residuals, the data were generated
+  # using a different error model, so no wonder
+  suppressWarnings(
+    fit_DFOP_par_c <- mkinfit(m_synth_DFOP_par,
+      synthetic_data_for_UBA_2014[[12]]$data,
+      quiet = TRUE)
+  )
 
   parms <- round(fit_DFOP_par_c$bparms.optim, c(1, 4, 4, 4, 4, 4, 4, 4))
-  expect_equal(parms, c(parent_0 = 103.0, 
+  expect_equal(parms, c(parent_0 = 103.0,
                         k_M1 = 0.0389, k_M2 = 0.0095,
                         f_parent_to_M1 = 0.5565, f_parent_to_M2 = 0.3784,
                         k1 = 0.3263, k2 = 0.0202, g = 0.7130))