psych
cor.plot()
car
, ellipse
, lattice
, mvtnorm
, rgl
wants <- c("car", "ellipse", "lattice", "mvtnorm", "rgl")
has <- wants %in% rownames(installed.packages())
if(any(!has)) install.packages(wants[!has])
mu <- c(1, 3)
sigma <- matrix(c(1, 0.6, 0.6, 1), nrow=2)
rng <- 2.5
N <- 50
X <- seq(mu[1]-rng*sigma[1, 1], mu[1]+rng*sigma[1, 1], length.out=N)
Y <- seq(mu[2]-rng*sigma[2, 2], mu[2]+rng*sigma[2, 2], length.out=N)
set.seed(123)
library(mvtnorm)
genZ <- function(x, y) { dmvnorm(cbind(x, y), mu, sigma) }
matZ <- outer(X, Y, FUN="genZ")
N <- 10
age <- rnorm(N, 30, 8)
sport <- abs(-0.25*age + rnorm(N, 60, 40))
weight <- -0.3*age -0.4*sport + 100 + rnorm(N, 0, 3)
wScale <- (weight-min(weight)) * (0.8 / abs(diff(range(weight)))) + 0.2
symbols(age, sport, circles=wScale, inch=0.6, fg=NULL, bg=rainbow(N),
main="Weight against age and sport")
See sunflowerplot()
and stars()
for altenative approaches.
par(cex.main=1.4, mar=c(2, 2, 4, 2) + 0.1)
persp(X, Y, matZ, xlab="x", ylab="y", zlab="Density", theta=5, phi=35,
main="2D-normal probability density")
library(rgl)
vecX <- rep(seq(-10, 10, length.out=10), times=10)
vecY <- rep(seq(-10, 10, length.out=10), each=10)
vecZ <- vecX*vecY
plot3d(vecX, vecY, vecZ, main="3D Scatterplot",
col="blue", type="h", aspect=TRUE)
spheres3d(vecX, vecY, vecZ, col="red", radius=2)
grid3d(c("x", "y+", "z"))
## not shown
Better looking plots similar to the following ones can be generated very easily based on the ggplot2
package.
Njk <- 25
P <- 2
Q <- 2
IQ <- rnorm(P*Q*Njk, mean=100, sd=15)
height <- rnorm(P*Q*Njk, mean=175, sd=7)
IV1 <- factor(rep(c("control", "treatment"), each=Q*Njk))
IV2 <- factor(rep(c("f", "m"), times=P*Njk))
myDf <- data.frame(IV1, IV2, IQ, height)
coplot(IQ ~ height | IV1*IV2, pch=16, data=myDf)
library(lattice)
res <- histogram(IQ ~ height | IV1*IV2, data=myDf,
main="Histograms per group")
print(res)
N <- 20
P <- 2
IV <- rep(c("CG", "T"), each=N/P)
age <- sample(18:35, N, replace=TRUE)
IQ <- round(rnorm(N, mean=rep(c(100, 115), each=N/P), sd=15))
rating <- round(0.4*IQ - 30 + rnorm(N, 0, 10), 1)
score <- round(-0.3*IQ + 0.7*age + rnorm(N, 0, 8), 1)
mvDf <- data.frame(IV, age, IQ, rating, score)
pairs(mvDf[c("age", "IQ", "rating", "score")], main="Scatter plot matrix",
pch=16, col=c("red", "blue")[unclass(mvDf$IV)])
myHist <- function(x, ...) { par(new=TRUE); hist(x, ..., main="") }
myEll <- function(x, y, nSegments=100, rad=1, ...) {
splLL <- split(data.frame(x, y), mvDf$IV)
CG <- data.matrix(splLL$CG)
TT <- data.matrix(splLL$T)
library(car)
dataEllipse(CG, level=0.5, col="red", center.pch=4,
plot.points=FALSE, add=TRUE)
dataEllipse(TT, level=0.5, col="blue", center.pch=4,
plot.points=FALSE, add=TRUE)
}
pairs(mvDf[c("age", "IQ", "rating", "score")], diag.panel=myHist,
upper.panel=myEll, main="Scatter plot matrix", pch=16,
col=c("red", "blue")[unclass(mvDf$IV)])
Illustrating the correlation matrix of several variables.
library(mvtnorm)
N <- 200
P <- 8
Q <- 2
Lambda <- matrix(round(runif(P*Q, min=-0.9, max=0.9), 1), nrow=P)
FF <- rmvnorm(N, mean=c(0, 0), sigma=diag(Q))
E <- rmvnorm(N, mean=rep(0, P), sigma=diag(P)*0.3)
X <- FF %*% t(Lambda) + E
corMat <- cor(X)
rownames(corMat) <- paste("X", 1:P, sep="")
colnames(corMat) <- paste("X", 1:P, sep="")
round(corMat, 2)
X1 X2 X3 X4 X5 X6 X7 X8
X1 1.00 0.48 -0.29 0.59 0.17 0.34 -0.33 -0.59
X2 0.48 1.00 -0.64 0.36 0.57 0.59 -0.12 -0.51
X3 -0.29 -0.64 1.00 0.02 -0.79 -0.51 -0.20 0.15
X4 0.59 0.36 0.02 1.00 -0.15 0.16 -0.54 -0.76
X5 0.17 0.57 -0.79 -0.15 1.00 0.50 0.26 -0.05
X6 0.34 0.59 -0.51 0.16 0.50 1.00 -0.04 -0.26
X7 -0.33 -0.12 -0.20 -0.54 0.26 -0.04 1.00 0.48
X8 -0.59 -0.51 0.15 -0.76 -0.05 -0.26 0.48 1.00
cmCol <- rev(heat.colors(nrow(corMat)))
cmRamp <- colorRampPalette(cmCol)
cols <- cmRamp(length(corMat))
heatmap(corMat, symm=TRUE, revC=TRUE, Rowv=NA, Colv=NA,
col=cols, RowSideColors=cmCol)
ggplot2
provides its own graphics system and many functions for multi-panel plots.googleVis
and plotly
create online interactive diagrams based on JavaScript libraries.rayshader
shows how to render advanced 3D scenestry(detach(package:car))
try(detach(package:carData))
try(detach(package:ellipse))
try(detach(package:mvtnorm))
# try(detach(package:rgl))
try(detach(package:lattice))
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