From 73e650114af77582238abf5273e63005e0b2287e Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Mon, 6 Mar 2017 17:00:48 +0100 Subject: Static documentation now built by pkgdown::build_site() --- docs/massart97ex3.html | 194 ------------------------------------------------- 1 file changed, 194 deletions(-) delete mode 100644 docs/massart97ex3.html (limited to 'docs/massart97ex3.html') diff --git a/docs/massart97ex3.html b/docs/massart97ex3.html deleted file mode 100644 index 7e4d510..0000000 --- a/docs/massart97ex3.html +++ /dev/null @@ -1,194 +0,0 @@ - - - - -massart97ex3. chemCal 0.1-37 - - - - - - - - - - - - - - - -
-
-
- chemCal 0.1-37 -
- -
-
-
-
- - -
-
- -
- -

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

- -
-
-

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)

-The following objects are masked from 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.
-
-
- - - - - -
-
- - -
- - \ No newline at end of file -- cgit v1.2.1