Fix inverse predictions for replicate measurements

For details, see NEWS.md

1 files changed, 30 insertions, 0 deletions

diff --git a/tests/testthat/test_compare_investr.R b/tests/testthat/test_compare_investr.R
new file mode 100644
index 0000000..6191c89
--- /dev/null
+++ b/tests/testthat/test_compare_investr.R
@@ -0,0 +1,30 @@
+context("Compare with investr::calibrate")
+
+library(chemCal)
+library(investr)
+
+test_that("Unweighted regressions give same results as investr::calibrate using the Wald method", {
+  compare_investr <- function(object, y_sample) {
+    pred_chemCal <- inverse.predict(object, y_sample)
+    pred_investr <- calibrate(object, y_sample, interval = "Wald")
+    expect_equivalent(pred_chemCal[["Prediction"]], 
+                      pred_investr$estimate)
+    expect_equivalent(pred_chemCal[["Standard Error"]], 
+                      pred_investr$se)
+    expect_equivalent(pred_chemCal[["Confidence Limits"]][1], 
+                      pred_investr$lower)  
+    expect_equivalent(pred_chemCal[["Confidence Limits"]][2],
+                      pred_investr$upper)  
+  }
+  m_tol <- lm(peak_area ~ amount, data = rl95_toluene)
+  compare_investr(m_tol, 1000)
+
+  m_din <- lm(y ~ x, din32645)
+  compare_investr(m_din, 5000)
+
+  m_m1 <- lm(y ~ x, massart97ex1)
+  compare_investr(m_m1, 15)
+
+  m_m3 <- lm(y ~ x, massart97ex3)
+  compare_investr(m_m3, 15)
+})