massart97ex3. chemCal 0.1-37

Usage

data(massart97ex3)

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Description

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Sample dataset from p. 188 to test the package.

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Format

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

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Source

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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.

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Examples

data(massart97ex3)
-attach(massart97ex3)
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-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)
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-Warning message:
-Assuming constant prediction variance even though model fit is weighted
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-
-
-# The following concords with the book p. 200
-inverse.predict(m, 15, ws = 1.67)  # 5.9 +- 2.5
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-$Prediction
-[1] 5.865367
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-$`Standard Error`
-[1] 0.8926109
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-$Confidence
-[1] 2.478285
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-$`Confidence Limits`
-[1] 3.387082 8.343652
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-inverse.predict(m, 90, ws = 0.145) # 44.1 +- 7.9
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-$Prediction
-[1] 44.06025
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-$`Standard Error`
-[1] 2.829162
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-$Confidence
-[1] 7.855012
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-$`Confidence Limits`
-[1] 36.20523 51.91526
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-
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-# The LOD is only calculated for models from unweighted regression
-# with this version of chemCal
-m0 <- lm(y ~ x) 
-lod(m0)
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-$x
-[1] 5.407085
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-$y
-       1 
-13.63911 
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-
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-# Limit of quantification from unweighted regression
-loq(m0)
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-$x
-[1] 13.97764
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-$y
-      1 
-30.6235 
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-
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-# 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)
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-$x
-[1] 7.346195
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-$y
-       1 
-17.90777 
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-# 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. 
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Calibration data from Massart et al. (1997), example 3

Usage

Description

Format

Source

Examples