R Dataset / Package robustbase / Animals2
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| Attachment | Size |
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| dataset-33388.csv | 1.3 KB |
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
| Documentation |
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On this Picostat.com statistics page, you will find information about the Animals2 data set which pertains to Brain and Body Weights for 65 Species of Land Animals. The Animals2 data set is found in the robustbase R package. Try to load the Animals2 data set in R by issuing the following command at the console data("Animals2"). This may load the data into a variable called Animals2. If R says the Animals2 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 with library("robustbase") followed by data("Animals2"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing Animals2 at the command-line which should display the entire dataset. 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 Animals2 R data set. The size of this file is about 1,333 bytes. Brain and Body Weights for 65 Species of Land AnimalsDescriptionA data frame with average brain and body weights for 62 species of land mammals and three others. Note that this is simply the union of UsageAnimals2 Format
NoteAfter loading the MASS package, the data set is simply constructed by
Rousseeuw and Leroy (1987)'s ‘brain’ data is the same as
MASS's SourceWeisberg, S. (1985) Applied Linear Regression. 2nd edition. Wiley, pp. 144–5. P. J. Rousseeuw and A. M. Leroy (1987) Robust Regression and Outlier Detection. Wiley, p. 57. ReferencesVenables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Forth Edition. Springer. Examples
data(Animals2)
## Sensible Plot needs doubly logarithmic scale
plot(Animals2, log = "xy")## Regression example plot:
plotbb <- function(bbdat) {
d.name <- deparse(substitute(bbdat))
plot(log(brain) ~ log(body), data = bbdat, main = d.name)
abline( lm(log(brain) ~ log(body), data = bbdat))
abline(MASS::rlm(log(brain) ~ log(body), data = bbdat), col = 2)
legend("bottomright", leg = c("lm", "rlm"), col=1:2, lwd=1, inset = 1/20)
}
plotbb(bbdat = Animals2)## The `same' plot for Rousseeuw's subset:
data(Animals, package = "MASS")
brain <- Animals[c(1:24, 26:25, 27:28),]
plotbb(bbdat = brain)lbrain <- log(brain)
plot(mahalanobis(lbrain, colMeans(lbrain), var(lbrain)),
main = "Classical Mahalanobis Distances")
mcd <- covMcd(lbrain)
plot(mahalanobis(lbrain,mcd$center,mcd$cov),
main = "Robust (MCD) Mahalanobis Distances")
-- Dataset imported from https://www.r-project.org. |
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