CODEWITHSUNDEEP
rplotcorrelation
Samo Jerom
Samo Jerom

Reputation: 2371

How to modify this Correlation Matrix plot?

I have the following codes to display a correlation matrix,

panel.cor <- function(x, y, digits=2, prefix="", cex.cor)
{
    usr <- par("usr"); on.exit(par(usr))
    par(usr = c(0, 1, 0, 1))
    r <- abs(cor(x, y))
    txt <- format(c(r, 0.123456789), digits=digits)[1]
    txt <- paste(prefix, txt, sep="")
    if(missing(cex.cor)) cex <- 0.8/strwidth(txt)

    test <- cor.test(x,y)
    # borrowed from printCoefmat
    Signif <- symnum(test$p.value, corr = FALSE, na = FALSE,
                  cutpoints = c(0, 0.001, 0.01, 0.05, 0.1, 1),
                  symbols = c("***", "**", "*", ".", " "))

    text(0.5, 0.5, txt, cex = cex * r)
    text(.8, .8, Signif, cex=cex, col=2)
}
pairs(USJudgeRatings[,c(2:3,6,1,7)],
  lower.panel=panel.smooth, upper.panel=panel.cor)

I want to modify the plot like:

  1. Have smaller blue dots as

    pairs(USJudgeRatings[,c(2:3,6,1,7)],
      main="xxx",
      pch=18,
      col="blue",
      cex=0.8)

  2. Include a histogram of the entries on the diagonal (as seen in enter link description here)

  3. Display the correlation and p-value as

    r=0.9;
p=0.001;

with values not stars.

There is a fitting line displayed for the scatter plot of the paired data. What is the method used for the fitting? Which line is defined the fitting as the codes shown above? And how to change the fitting method?

Upvotes: 8

Views: 23391

Answers (2)

cgtydmrc
cgtydmrc

Reputation: 1

Modified Scatter Plot Matrix

  1. %% Modified function for histogram;

    panel.hist <- function(x, ...)
{
usr <- par("usr"); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
par(cex.axis=2, family="Times New Roman", face="bold", size=12, cex.lab=1, cex.main=1, cex.sub=1)
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col="cyan", ...)

}

  2. %% Modified Regression Function with panel.smooth;

    panel.smooth<-function (x, y, col = "black", bg = NA, pch = 16, 
                cex = 2, col.smooth = "red", span = 2/3, iter = 3, ...) 
{
points(x, y, pch = pch, col = col, bg = bg, cex = cex)
ok <- is.finite(x) & is.finite(y)
if (any(ok)) 
lines(stats::lowess(x[ok], y[ok], f = span, iter = iter), 
      col = col.smooth, ...)
}

  3. %% Modified Correlation Function with panel.cor;

    panel.cor <- function(x, y, digits=2, cex.cor)
{
usr <- par("usr"); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
r <- abs(cor(x, y))
txt <- format(c(r, 0.123456789), digits=digits)[1]
test <- cor.test(x,y)
Signif <- ifelse(round(test$p.value,3)<0.001,"p < 0.001",paste("p = ",round(test$p.value,3)))  
text(0.5, 0.25, paste("r = ",txt), cex = 2.5, family="Times New Roman", face="bold", size=12)
text(.5, .75, Signif, cex = 2.5, family="Times New Roman", face="bold", size=12)
}

To be able to plot the scatterplot matrix, you also need to install "Times New Roman" font. To do it, follow the steps below;

  1. %% Install all fonts into RStudio. This is important to improve the quality of the plot!

    install.packages("extrafont") # Install fonts
library(extrafont)            # Install library
font_import()                 # Import all fonts  
loadfonts(device="win")       # Register fonts for Windows bitmap output
fonts()                       # Finish the process

  2. %% Finally, plot your figure with pairs function;

     pairs(qq1, lower.panel=panel.smooth, upper.panel=panel.cor ,diag.panel=panel.hist, cex = 2, cex.labels = 2, cex.main = 2)

  3. %% Check the final product; enter image description here

Upvotes: 0

Didzis Elferts
Didzis Elferts

Reputation: 98449

Help page for the function pairs() gives you example how to define panels to plot.

For your particular case:

Changed panel.cor() function to show to lines of text - p-values and correlation coefficients.

panel.cor <- function(x, y, digits=2, cex.cor)
{
  usr <- par("usr"); on.exit(par(usr))
  par(usr = c(0, 1, 0, 1))
  r <- abs(cor(x, y))
  txt <- format(c(r, 0.123456789), digits=digits)[1]
  test <- cor.test(x,y)
  Signif <- ifelse(round(test$p.value,3)<0.001,"p<0.001",paste("p=",round(test$p.value,3)))  
  text(0.5, 0.25, paste("r=",txt))
  text(.5, .75, Signif)
}

For panel.smooth() function defined cex=, col= and pch= arguments.

panel.smooth<-function (x, y, col = "blue", bg = NA, pch = 18, 
                        cex = 0.8, col.smooth = "red", span = 2/3, iter = 3, ...) 
{
  points(x, y, pch = pch, col = col, bg = bg, cex = cex)
  ok <- is.finite(x) & is.finite(y)
  if (any(ok)) 
    lines(stats::lowess(x[ok], y[ok], f = span, iter = iter), 
          col = col.smooth, ...)
}

To add histograms, panel.hist() functions should be defined (taken from help file of pairs())

panel.hist <- function(x, ...)
{
  usr <- par("usr"); on.exit(par(usr))
  par(usr = c(usr[1:2], 0, 1.5) )
  h <- hist(x, plot = FALSE)
  breaks <- h$breaks; nB <- length(breaks)
  y <- h$counts; y <- y/max(y)
  rect(breaks[-nB], 0, breaks[-1], y, col="cyan", ...)
}

Final plot:

pairs(USJudgeRatings[,c(2:3,6,1,7)],
          lower.panel=panel.smooth, upper.panel=panel.cor,diag.panel=panel.hist)

enter image description here

Upvotes: 37

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