Das lattice-Paket
It is designed to meet most typical graphics needs with minimal tuning, but can also be easily extended to handle most nonstandard requirements.
http://stat.ethz.ch/R-manual/R-devel/library/lattice/html/Lattice.html
Histogramm mit Lattice
library("lattice")
library("mlmRev")
data(Chem97)
histogram(~ gcsescore, data = Chem97)
Histogramm mit Lattice
histogram(~ gcsescore | factor(score),data = Chem97)
Die Dichte mit Lattice zeichnen
densityplot(~ gcsescore | factor(score), Chem97,
groups=gender,plot.points=FALSE,auto.key=TRUE)
Einführung in das Paket lattice
Boxplot mit Lattice zeichnen
bwplot(factor(score) ~ gcsescore | gender, Chem97)
Boxplot mit Lattice zeichnen
bwplot(gcsescore ~ gender | factor(score), Chem97,
layout = c(6, 1))
Univariate Plots
barchart(yield ~ variety | site, data = barley,
groups = year, layout = c(1,6), stack = TRUE,
auto.key = list(space = "right"),
ylab = "Barley Yield (bushels/acre)",
scales = list(x = list(rot = 45)))
Densityplot
densityplot( ~ height | voice.part, data = singer, layout = c(2, 4),
xlab = "Height (inches)", bw = 5)
Bivariate Plots
qq(gender ~ gcsescore | factor(score), Chem97,
f.value = ppoints(100), type = c("p", "g"), aspect = 1)
xyplot
xyplot(Sepal.Length + Sepal.Width ~ Petal.Length + Petal.Width | Species,
data = iris, scales = "free", layout = c(2, 2),
auto.key = list(x = .6, y = .7, corner = c(0, 0)))
Multivariate Plots
splom(~iris[1:4], groups = Species, data = iris)
super.sym <- trellis.par.get("superpose.symbol")
splom(~iris[1:4], groups = Species, data = iris,
panel = panel.superpose,
key = list(title = "Three Varieties of Iris",
columns = 3,
points = list(pch = super.sym$pch[1:3],
col = super.sym$col[1:3]),
text = list(c("Setosa", "Versicolor", "Virginica"))))
parallelplot
parallelplot(~iris[1:4] | Species, iris)
