From d8d6012e98fb4c7f158bcc7c173407c2b5f3e42e Mon Sep 17 00:00:00 2001 From: ranke Date: Sat, 22 Aug 2015 09:03:10 +0000 Subject: Get rid of the branched svn layout I never used git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@36 5fad18fb-23f0-0310-ab10-e59a3bee62b4 --- tests/massart97.Rout.save | 128 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 128 insertions(+) create mode 100644 tests/massart97.Rout.save (limited to 'tests/massart97.Rout.save') diff --git a/tests/massart97.Rout.save b/tests/massart97.Rout.save new file mode 100644 index 0000000..ce99c30 --- /dev/null +++ b/tests/massart97.Rout.save @@ -0,0 +1,128 @@ + +R version 3.1.0 (2014-04-10) -- "Spring Dance" +Copyright (C) 2014 The R Foundation for Statistical Computing +Platform: x86_64-pc-linux-gnu (64-bit) + +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. + +> require(chemCal) +Loading required package: chemCal +> data(massart97ex1) +> m <- lm(y ~ x, data = massart97ex1) +> inverse.predict(m, 15) # 6.1 +- 4.9 +$Prediction +[1] 6.09381 + +$`Standard Error` +[1] 1.767278 + +$Confidence +[1] 4.906751 + +$`Confidence Limits` +[1] 1.187059 11.000561 + +> inverse.predict(m, 90) # 43.9 +- 4.9 +$Prediction +[1] 43.93983 + +$`Standard Error` +[1] 1.767747 + +$Confidence +[1] 4.908053 + +$`Confidence Limits` +[1] 39.03178 48.84788 + +> inverse.predict(m, rep(90,5)) # 43.9 +- 3.2 +$Prediction +[1] 43.93983 + +$`Standard Error` +[1] 1.141204 + +$Confidence +[1] 3.168489 + +$`Confidence Limits` +[1] 40.77134 47.10832 + +> +> 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) +> #calplot(m) +> +> inverse.predict(m, 15, ws = 1.67) # 5.9 +- 2.5 +$Prediction +[1] 5.865367 + +$`Standard Error` +[1] 0.8926109 + +$Confidence +[1] 2.478285 + +$`Confidence Limits` +[1] 3.387082 8.343652 + +> inverse.predict(m, 90, ws = 0.145) # 44.1 +- 7.9 +$Prediction +[1] 44.06025 + +$`Standard Error` +[1] 2.829162 + +$Confidence +[1] 7.855012 + +$`Confidence Limits` +[1] 36.20523 51.91526 + +> +> m0 <- lm(y ~ x) +> lod(m0) +$x +[1] 5.407085 + +$y + 1 +13.63911 + +> +> loq(m0) +$x +[1] 13.97764 + +$y + 1 +30.6235 + +> loq(m, w.loq = 1.67) +$x +[1] 7.346195 + +$y + 1 +17.90777 + +> +> proc.time() + user system elapsed + 0.529 0.327 0.443 -- cgit v1.2.1