corrplot | R Documentation |
Function for making a correlation plot starting from a data matrix
corrplot (data, varnames=NULL, cutpts=NULL,
abs=TRUE, details=TRUE,
n.col.legend=5, cex.col=0.7,
cex.var=0.9, digits=1, color=FALSE)
data |
a data matrix |
varnames |
variable names of the data matrix, if not provided use default variable names |
abs |
if TRUE, transform all correlation values into positive values, default=TRUE. |
cutpts |
a vector of cutting points for color legend, default is NULL. The function will decide the cutting points if cutpts is not assigned. |
details |
show more than one digits correlaton values. Default is TRUE. FALSE is suggested to get readable output. |
n.col.legend |
number of legend for the color thermometer. |
cex.col |
font size of the color thermometer. |
cex.var |
font size of the variable names. |
digits |
number of digits shown in the text of the color theromoeter. |
color |
color of the plot, default is FALSE, which uses gray scale. |
The function adapts the R function for Figure 8 in Tian Zheng, Matthew Salganik, and Andrew Gelman, 2006, "How many people do you know in prison?: using overdispersion in count data to estimate social structure in networks", Journal of the American Statistical Association, Vol.101, N0. 474: p.409-23.
A correlation plot.
Tian Zheng tzheng@stat.columbia.edu; Yu-Sung Su suyusung@tsinghua.edu.cn
Tian Zheng, Matthew Salganik, and Andrew Gelman, 2006, "How many people do you know in prison?: using overdispersion in count data to estimate social structure in networks", Journal of the American Statistical Association, Vol.101, N0. 474: p.409-23
cor
,
par
old.par <- par(no.readonly = TRUE)
x1 <- rnorm(1000,50,2)
x2 <- rbinom(1000,1,prob=0.63)
x3 <- rpois(1000, 2)
x4 <- runif(1000,40,100)
x5 <- rnorm(1000,100,30)
x6 <- rbeta(1000,2,2)
x7 <- rpois(1000,10)
x8 <- rbinom(1000,1,prob=0.4)
x9 <- rbeta(1000,5,4)
x10 <- runif(1000,-10,-1)
test.data <- data.matrix(cbind(x1,x2,x3,x4,x5,x6,x7,x8,x9,x10))
test.names <- c("a short name01","a short name02","a short name03",
"a short name04","a short name05","a short name06",
"a short name07","a short name08","a short name09",
"a short name10")
# example 1
corrplot(test.data)
# example 2
corrplot(test.data,test.names, abs=FALSE, n.col.legend=7)
corrplot(test.data,test.names, abs=TRUE, n.col.legend=7)
# example 3
data(lalonde)
corrplot(lalonde, details=FALSE, color=TRUE)
corrplot(lalonde, cutpts=c(0,0.25,0.5,0.75), color=TRUE, digits=2)
par(old.par)
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