massart97ex3. chemCal 0.1-35.900

Usage

data(massart97ex3)

+ +

Description

+ +

Sample dataset from p. 188 to test the package.

+ +

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

data(massart97ex3)
+attach(massart97ex3)
+
+Die folgenden Objekte sind maskiert von massart97ex3 (pos = 3):
+
+    x, y
+
+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)
+
+Warning message:
+Assuming constant prediction variance even though model fit is weighted
+
+
+
+# The following concords with the book p. 200
+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
+
+
+
+# The LOD is only calculated for models from unweighted regression
+# with this version of chemCal
+m0 <- lm(y ~ x) 
+lod(m0)
+
+$x
+[1] 5.407085
+
+$y
+       1 
+13.63911 
+
+
+
+# Limit of quantification from unweighted regression
+loq(m0)
+
+$x
+[1] 13.97764
+
+$y
+      1 
+30.6235 
+
+
+
+# For calculating the limit of quantification from a model from weighted
+# regression, we need to supply weights, internally used for inverse.predict
+# If we are not using a variance function, we can use the weight from
+# the above example as a first approximation (x = 15 is close to our
+# loq approx 14 from above).
+loq(m, w.loq = 1.67)
+
+$x
+[1] 7.346195
+
+$y
+       1 
+17.90777 
+
+
+# The weight for the loq should therefore be derived at x = 7.3 instead
+# of 15, but the graphical procedure of Massart (p. 201) to derive the 
+# variances on which the weights are based is quite inaccurate anyway. 
+

+ + + +

Calibration data from Massart et al. (1997), example 3

Usage

Description

Format

Source

Examples