R Dataset / Package robustbase / kootenay

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Embed
<iframe src="https://embed.picostat.com/r-dataset-package-robustbase-kootenay.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-84799.csv 142 bytes
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the kootenay data set which pertains to Waterflow Measurements of Kootenay River in Libby and Newgate. The kootenay data set is found in the robustbase R package. You can load the kootenay data set in R by issuing the following command at the console data("kootenay"). This will load the data into a variable called kootenay. If R says the kootenay data set is not found, you can try installing the package by issuing this command install.packages("robustbase") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the kootenay R data set. The size of this file is about 142 bytes.

Documentation

Waterflow Measurements of Kootenay River in Libby and Newgate

Description

The original data set is the waterflow in January of the Kootenay river, measured at two locations, namely, Libby (Montana) and Newgate (British Columbia) for 13 consecutive years, 1931–1943.

The data set is of mostly interest because it has been used as example in innumerous didactical situations about robust regression. To this end, one number (in observation 4) has been modified from the original data from originally 44.9 to 15.7 (here).

Usage

data(kootenay)

Format

A data frame with 13 observations on the following 2 variables.

Libby

a numeric vector

Newgate

a numeric vector

Details

The original (unmodified) version of the data is easily obtainable as kootenay0 from the examples; other modified versions of the data sets are also used in different places, see the examples below.

Source

Original Data, p.58f of Ezekiel and Fox (1959), Methods of Correlation and Regression Analysis. Wiley, N.Y.

References

Hampel, F., Ronchetti, E., Rousseeuw, P. and Stahel, W. (1986) Robust Statistics: The Approach Based on Influence Functions; Wiley, N.Y.

Rousseeuw, P. J. and Leroy, A. M. (1987) Robust Regression & Outlier Detection, Wiley, N. Y.

Examples

data(kootenay)
plot(kootenay, main = "'kootenay' data")
points(kootenay[4,], col = 2, cex =2, pch = 3)abline(lm   (Newgate ~ Libby, data = kootenay), col = "pink")
abline(lmrob(Newgate ~ Libby, data = kootenay), col = "blue")## The original version of Ezekiel & Fox:
kootenay0 <- kootenay
kootenay0[4, "Newgate"] <- 44.9
plot(kootenay0, main = "'kootenay0': the original data")
abline(lm   (Newgate ~ Libby, data = kootenay0), col = "pink")
abline(lmrob(Newgate ~ Libby, data = kootenay0), col = "blue")## The version with "milder" outlier -- Hampel et al., p.310
kootenay2 <- kootenay0
kootenay2[4, "Libby"] <- 20.0 # instead of 77.6
plot(kootenay2, main = "The 'kootenay2' data",
     xlim = range(kootenay[,"Libby"]))
points(kootenay2[4,], col = 2, cex =2, pch = 3)
abline(lm   (Newgate ~ Libby, data = kootenay2), col = "pink")
abline(lmrob(Newgate ~ Libby, data = kootenay2), col = "blue")
--

Dataset imported from https://www.r-project.org.

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