Question

我有以下代码来显示相关矩阵

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)

我想修改情节，如：

有更小的蓝点

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

在对角线上包含条目的直方图（如enter link description here所示）
将相关性和p值显示为
```
r=0.9;
p=0.001;
```

值不是星星。

显示配对数据的散点图的拟合线。拟合的方法是什么？哪条线被定义为上面显示的代码？以及如何改变拟合方法？

Answer 1

函数pairs()的帮助页面为您提供了如何定义要绘制的面板的示例。

针对您的具体情况：

更改panel.cor()函数以显示文本行 - p值和相关系数。

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)
}

panel.smooth()函数定义cex=，col=和pch=参数。

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, ...)
}

要添加直方图，应定义panel.hist()函数（取自pairs()的帮助文件）

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", ...)
}

最终情节：

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

enter image description here

Answer 2

修改的散点图矩阵

%%直方图的修改函数;

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", ...)

}

%%使用panel.smooth修改了回归函数;

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, ...)
}

%%修改后的相关函数与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)
}

为了能够绘制散点图矩阵，还需要安装“Times New Roman”字体。为此，请按照以下步骤操作;

%%将所有字体安装到RStudio中。这对提高情节质量很重要！

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

%%最后，使用pairs函数绘制您的数字;

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

%%检查最终产品; enter image description here

如何修改此相关矩阵图？

2 个答案: