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R : Copyright 2006, The R Foundation for Statistical Computing
Version 2.3.0 (2006-04-24)
ISBN 3-900051-07-0

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Type 'contributors()' for more information and
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> library(chemCal)
> 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)
> # The following concords with the book
> inverse.predict(m, 15, ws = 1.67)
$Prediction
[1] 5.865367

$`Standard Error`
[1] 0.892611

$Confidence
[1] 2.478285

$`Confidence Limits`
[1] 3.387082 8.343652

> inverse.predict(m, 90, ws = 0.145)
$Prediction
[1] 44.06025

$`Standard Error`
[1] 2.829162

$Confidence
[1] 7.855012

$`Confidence Limits`
[1] 36.20523 51.91526

>

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