From 43d58935483e0d9dda7a74c029e7d7d2adad9ed7 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 20 May 2020 08:44:47 +0200 Subject: Static documentation rebuilt by pkgdown::build_site() --- docs/reference/massart97ex3.html | 84 ++++++++++++++++++++++------------------ 1 file changed, 46 insertions(+), 38 deletions(-) (limited to 'docs/reference/massart97ex3.html') diff --git a/docs/reference/massart97ex3.html b/docs/reference/massart97ex3.html index c1bbbc2..a1efeba 100644 --- a/docs/reference/massart97ex3.html +++ b/docs/reference/massart97ex3.html @@ -8,21 +8,29 @@ Calibration data from Massart et al. (1997), example 3 — massart97ex3 • chemCal + - + - - + + + + + + + - + + - + - - + + + @@ -30,10 +38,10 @@ - + - + @@ -47,9 +55,10 @@ + - +
@@ -95,6 +108,7 @@
+
@@ -106,38 +120,35 @@
-

Sample dataset from p. 188 to test the package.

- 
massart97ex3
- + +

Format

A dataframe containing 6 levels of x values with 5 observations of y for each level.

-

Source

Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A, Chapter 8.

-

Examples

# For reproducing the results for replicate standard measurements in example 8,
 # we need to do the calibration on the means when using chemCal > 0.2
-weights <- with(massart97ex3, {
-  yx <- split(y, x)
-  ybar <- sapply(yx, mean)
-  s <- round(sapply(yx, sd), digits = 2)
-  w <- round(1 / (s^2), digits = 3)
+weights <- with(massart97ex3, {
+  yx <- split(y, x)
+  ybar <- sapply(yx, mean)
+  s <- round(sapply(yx, sd), digits = 2)
+  w <- round(1 / (s^2), digits = 3)
 })
 
-massart97ex3.means <- aggregate(y ~ x, massart97ex3, mean)
+massart97ex3.means <- aggregate(y ~ x, massart97ex3, mean)
 
-m3.means <- lm(y ~ x, w = weights, data = massart97ex3.means)
+m3.means <- lm(y ~ x, w = weights, data = massart97ex3.means)
 
 # The following concords with the book p. 200
 inverse.predict(m3.means, 15, ws = 1.67)  # 5.9 +- 2.5
#> $Prediction
@@ -165,7 +176,7 @@
 #> 

 # The LOD is only calculated for models from unweighted regression
 # with this version of chemCal
-m0 <- lm(y ~ x, data = massart97ex3)
+m0 <- lm(y ~ x, data = massart97ex3)
 lod(m0)
#> $x
 #> [1] 5.407085
 #> 
@@ -194,33 +205,30 @@
 # variances on which the weights are based is quite inaccurate anyway.
- + + + -- cgit v1.2.1