R Dataset / Package DAAG / frogs

On this R-data statistics page, you will find information about the frogs data set which pertains to Frogs Data. The frogs data set is found in the DAAG R package. You can load the frogs data set in R by issuing the following command at the console data("frogs"). This will load the data into a variable called frogs. If R says the frogs 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 frogs R data set. The size of this file is about 12,680 bytes.

Frogs Data

Description

The frogs data frame has 212 rows and 11 columns. The data are on the distribution of the Southern Corroboree frog, which occurs in the Snowy Mountains area of New South Wales, Australia.

Usage

frogs

Format

This data frame contains the following columns:

pres.abs: 0 = frogs were absent, 1 = frogs were present
northing: reference point
easting: reference point
altitude: altitude , in meters
distance: distance in meters to nearest extant population
NoOfPools: number of potential breeding pools
NoOfSites: (number of potential breeding sites within a 2 km radius
avrain: mean rainfall for Spring period
meanmin: mean minimum Spring temperature
meanmax: mean maximum Spring temperature

Source

Hunter, D. (2000) The conservation and demography of the southern corroboree frog (Pseudophryne corroboree). M.Sc. thesis, University of Canberra, Canberra.

Examples

print("Multiple Logistic Regression - Example 8.2")plot(northing ~ easting, data=frogs, pch=c(1,16)[frogs$pres.abs+1],
xlab="Meters east of reference point", ylab="Meters north")
pairs(frogs[,4:10])
attach(frogs)
pairs(cbind(altitude,log(distance),log(NoOfPools),NoOfSites),
panel=panel.smooth, labels=c("altitude","log(distance)",
"log(NoOfPools)","NoOfSites"))
detach(frogs)frogs.glm0 <- glm(formula = pres.abs ~ altitude + log(distance) +
log(NoOfPools) + NoOfSites + avrain + meanmin + meanmax,
family = binomial, data = frogs)
summary(frogs.glm0)frogs.glm <- glm(formula = pres.abs ~ log(distance) + log(NoOfPools) + 
meanmin +
meanmax, family = binomial, data = frogs)
oldpar <- par(mfrow=c(2,2))
termplot(frogs.glm, data=frogs)termplot(frogs.glm, data=frogs, partial.resid=TRUE)cv.binary(frogs.glm0) # All explanatory variables
pause()cv.binary(frogs.glm)# Reduced set of explanatory variablesfor (j in 1:4){
 rand <- sample(1:10, 212, replace=TRUE)
 all.acc <- cv.binary(frogs.glm0, rand=rand, print.details=FALSE)$acc.cv
 reduced.acc <- cv.binary(frogs.glm, rand=rand, print.details=FALSE)$acc.cv
 cat("\nAll:", round(all.acc,3), "Reduced:", round(reduced.acc,3))
}

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

Attachments: csv, json

<iframe src="https://pmagunia.com/iframe/r-dataset-package-daag-frogs.html" width="100%" height="100%" style="border:0px"></iframe>

On Things