Don't do calplot and lod for linear models from weighted

regression any more, since this is not supported (PR#8877).



git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@13 5fad18fb-23f0-0310-ab10-e59a3bee62b4

4 files changed, 116 insertions, 0 deletions

diff --git a/tests/din32645.R b/tests/din32645.R
new file mode 100644
index 0000000..dc0aee6
--- /dev/null
+++ b/tests/din32645.R
@@ -0,0 +1,7 @@
+library(chemCal)
+data(din32645)
+m <- lm(y ~ x, data=din32645)
+inverse.predict(m,3500,alpha=0.01)
+lod <- lod(m, alpha = 0.01, beta = 0.5)
+lod(m, alpha = 0.01, beta = 0.01) 
+loq <- loq(m, alpha = 0.01)
diff --git a/tests/din32645.Rout.save b/tests/din32645.Rout.save
new file mode 100644
index 0000000..10cd1ab
--- /dev/null
+++ b/tests/din32645.Rout.save
@@ -0,0 +1,43 @@
+
+R : Copyright 2006, The R Foundation for Statistical Computing
+Version 2.3.0 (2006-04-24)
+ISBN 3-900051-07-0
+
+R is free software and comes with ABSOLUTELY NO WARRANTY.
+You are welcome to redistribute it under certain conditions.
+Type 'license()' or 'licence()' for distribution details.
+
+R is a collaborative project with many contributors.
+Type 'contributors()' for more information and
+'citation()' on how to cite R or R packages in publications.
+
+Type 'demo()' for some demos, 'help()' for on-line help, or
+'help.start()' for an HTML browser interface to help.
+Type 'q()' to quit R.
+
+> library(chemCal)
+> data(din32645)
+> m <- lm(y ~ x, data=din32645)
+> inverse.predict(m,3500,alpha=0.01)
+$Prediction
+[1] 0.1054792
+
+$`Standard Error`
+[1] 0.02215619
+
+$Confidence
+[1] 0.07434261
+
+$`Confidence Limits`
+[1] 0.03113656 0.17982178
+
+> lod <- lod(m, alpha = 0.01, beta = 0.5)
+> lod(m, alpha = 0.01, beta = 0.01) 
+$x
+[1] 0.132904
+
+$y
+[1] 3764.977
+
+> loq <- loq(m, alpha = 0.01)
+> 
diff --git a/tests/massart97.R b/tests/massart97.R
new file mode 100644
index 0000000..7170ec4
--- /dev/null
+++ b/tests/massart97.R
@@ -0,0 +1,12 @@
+library(chemCal)
+data(massart97ex3)
+attach(massart97ex3)
+yx <- split(y,x)
+ybar <- sapply(yx,mean)
+s <- round(sapply(yx,sd),digits=2)
+w <- round(1/(s^2),digits=3)
+weights <- w[factor(x)]
+m <- lm(y ~ x,w=weights)
+# The following concords with the book
+inverse.predict(m, 15, ws = 1.67)
+inverse.predict(m, 90, ws = 0.145)
diff --git a/tests/massart97.Rout.save b/tests/massart97.Rout.save
new file mode 100644
index 0000000..ae50275
--- /dev/null
+++ b/tests/massart97.Rout.save
@@ -0,0 +1,54 @@
+
+R : Copyright 2006, The R Foundation for Statistical Computing
+Version 2.3.0 (2006-04-24)
+ISBN 3-900051-07-0
+
+R is free software and comes with ABSOLUTELY NO WARRANTY.
+You are welcome to redistribute it under certain conditions.
+Type 'license()' or 'licence()' for distribution details.
+
+R is a collaborative project with many contributors.
+Type 'contributors()' for more information and
+'citation()' on how to cite R or R packages in publications.
+
+Type 'demo()' for some demos, 'help()' for on-line help, or
+'help.start()' for an HTML browser interface to help.
+Type 'q()' to quit R.
+
+> library(chemCal)
+> data(massart97ex3)
+> attach(massart97ex3)
+> yx <- split(y,x)
+> ybar <- sapply(yx,mean)
+> s <- round(sapply(yx,sd),digits=2)
+> w <- round(1/(s^2),digits=3)
+> weights <- w[factor(x)]
+> m <- lm(y ~ x,w=weights)
+> # The following concords with the book
+> inverse.predict(m, 15, ws = 1.67)
+$Prediction
+[1] 5.865367
+
+$`Standard Error`
+[1] 0.892611
+
+$Confidence
+[1] 2.478285
+
+$`Confidence Limits`
+[1] 3.387082 8.343652
+
+> inverse.predict(m, 90, ws = 0.145)
+$Prediction
+[1] 44.06025
+
+$`Standard Error`
+[1] 2.829162
+
+$Confidence
+[1] 7.855012
+
+$`Confidence Limits`
+[1] 36.20523 51.91526
+
+>