R package installation and administration

A short list of basic but useful commands for managing
the packages in R:

# install a package
install.packages("ROCR")
# visualize package version
package_version("pamr")
# update a package
update.packages("Cairo")
# remove a package
remove.packages("RGtk2")

Sorting/ordering a data.frame according specific columns


x = rnorm(20)
y = sample(rep(1:2, each = 10))
z = sample(rep(1:4, 5))

data.df <- data.frame(values = x, labels.1 = y, labels.2 = z)
print(data.df)

# data ordered according to "labels.1" column
# and then "labels.2" column
nams <- c("labels.1", "labels.2")
data.df.sorted = data.df[do.call(order, data.df[nams]), ]
print(data.df.sorted)


Receiver Operating Characteristic (ROC) Curve in ROCR and verification packages

The following VERY basic code shows how to plot a simple ROC Curve both by means of ROCR package and by verification package.

# it allows two different plots in the same frame
par(mfrow = c(1,2))
# plot a ROC curve for a single prediction run
# and color the curve according to cutoff.
library(ROCR)
data(ROCR.simple)
pred <- prediction(ROCR.simple$predictions, ROCR.simple$labels)
perf <- performance(pred,"tpr", "fpr")
plot(perf,colorize = TRUE)
# plot a ROC curve for a single prediction run
# with CI by bootstrapping and fitted curve
library(verification)
roc.plot(ROCR.simple$labels,ROCR.simple$predictions, xlab = "False positive rate",
ylab = "True positive rate", main = NULL, CI = T, n.boot = 100, plot = "both", binormal = TRUE)