R Dataset / Package DAAG / leafshape17

On this R-data statistics page, you will find information about the leafshape17 data set which pertains to Subset of Leaf Shape Data Set. The leafshape17 data set is found in the DAAG R package. You can load the leafshape17 data set in R by issuing the following command at the console data("leafshape17"). This will load the data into a variable called leafshape17. If R says the leafshape17 data set is not found, you can try installing the package by issuing this command install.packages("DAAG") and then attempt to reload the data with the library() command. 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 leafshape17 R data set. The size of this file is about 4,883 bytes.

Subset of Leaf Shape Data Set

Description

The leafshape17 data frame has 61 rows and 8 columns. These are leaf length, width and petiole measurements taken at several sites in Australia. This is a subset of the leafshape data frame.

Usage

leafshape17

Format

This data frame contains the following columns:

bladelen: leaf length (in mm)
petiole: a numeric vector
bladewid: leaf width (in mm)
latitude: latitude
logwid: natural logarithm of width
logpet: logarithm of petiole measurement
loglen: logarithm of length
arch: leaf architecture (0 = orthotropic, 1 = plagiotropic)

Source

King, D.A. and Maindonald, J.H. 1999. Tree architecture in relation to leaf dimensions and tree stature in temperate and tropical rain forests. Journal of Ecology 87: 1012-1024.

Examples

print("Discriminant Analysis - Example 11.2")require(MASS)
leaf17.lda <- lda(arch ~ logwid+loglen, data=leafshape17)
leaf17.hat <- predict(leaf17.lda)
leaf17.lda
 table(leafshape17$arch, leaf17.hat$class)
pause()tab <- table(leafshape17$arch, leaf17.hat$class)
 sum(tab[row(tab)==col(tab)])/sum(tab)
leaf17cv.lda <- lda(arch ~ logwid+loglen, data=leafshape17, CV=TRUE)
tab <- table(leafshape17$arch, leaf17cv.lda$class)
pause()leaf17.glm <- glm(arch ~ logwid + loglen, family=binomial, data=leafshape17)
 options(digits=3)
summary(leaf17.glm)$coef
pause()leaf17.one <- cv.binary(leaf17.glm)
table(leafshape17$arch, round(leaf17.one$internal)) # Resubstitution
pause()table(leafshape17$arch, round(leaf17.one$cv)) # Cross-validation

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

Attachments: csv, json

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