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triangleplot

Triangle Plot


Description

Function for making a triangle plot from a square matrix

Usage

triangleplot (x, y=NULL, cutpts=NULL, details=TRUE, 
            n.col.legend=5, cex.col=0.7, 
            cex.var=0.9, digits=1, color=FALSE)

Arguments

x

a square matrix.

y

a vector of names that corresponds to each element of the square matrix x.

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.

Details

The function makes a triangle plot from a square matrix, e.g., the correlation plot, see corrplot. If a square matrix contains missing values, the cells of missing values will be marked x.

Author(s)

See Also

Examples

old.par <- par(no.readonly = TRUE)

 # create a square matrix
 x <- matrix(runif(1600, 0, 1), 40, 40)
 
 # fig 1
 triangleplot(x)
 
 # fig 2 assign cutting points
 triangleplot(x, cutpts=c(0,0.25,0.5,0.75,1), digits=2)
 
 # fig 3 if x contains missing value
 x[12,13] <- x[13,12] <- NA
 x[25,27] <- x[27,25] <- NA
 triangleplot(x)
 
par(old.par)

#
#library(RColorBrewer)
#cormat <-  cor(iris[,-5])
#triangleplot2(cormat,color = brewer.pal( 5, "RdBu" ),
# n.col.legend=5, cex.col=0.7, cex.var=0.5)

arm

Data Analysis Using Regression and Multilevel/Hierarchical Models

v1.11-2
GPL (> 2)
Authors
Andrew Gelman [aut], Yu-Sung Su [aut, cre], Masanao Yajima [ctb], Jennifer Hill [ctb], Maria Grazia Pittau [ctb], Jouni Kerman [ctb], Tian Zheng [ctb], Vincent Dorie [ctb]
Initial release
2020-7-27

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