使用 R corrplot,我还没有找到将框中的相关系数及其显着性绘制在一起的解决方案,即 0.84*** 这是仅绘制重要性星星的代码。如何在那里添加相关系数?
M<-cor(mtcars)
res1 <- cor.mtest(mtcars, conf.level = .95)
corrplot(cor(mtcars),
method="square",
type="lower",
p.mat = res1$p,
insig = "label_sig",
sig.level = c(.001, .01, .05),
pch.cex = 0.8,
pch.col = "red",
tl.col="black",
tl.cex=1,
outline=TRUE)
如果我按照第一个答案的建议添加addCoef.col =“black”, 文本覆盖了重要的星星,因此它们实际上不再可见:
重要性星星的位置由
place_points
函数内的 corrplot
函数定义。
如果两者都应显示相关系数和显着性水平,则它们会重叠(我用黄色表示星星,因为我的色觉有一些问题......)。
library(corrplot)
#> corrplot 0.90 loaded
M<-cor(mtcars)
res1 <- cor.mtest(mtcars, conf.level = .95)
corrplot(cor(mtcars),
method="square",
type="lower",
p.mat = res1$p,
insig = "label_sig",
sig.level = c(.001, .01, .05),
pch.cex = 0.8,
pch.col = "yellow",
tl.col="black",
tl.cex=1,
addCoef.col = "black",
tl.pos="n",
outline=TRUE)
由 reprex 包于 2021 年 10 月 13 日创建(v2.0.1)
更改
place_points
函数内的 corrplot
函数。为此,请运行:
trace(corrplot, edit=TRUE)
然后替换到443行
place_points = function(sig.locs, point) {
text(pos.pNew[, 1][sig.locs], pos.pNew[, 2][sig.locs],
labels = point, col = pch.col, cex = pch.cex,
lwd = 2)
与:
# adjust text(X,Y ...) according to your needs, here +0.25 is added to the Y-position
place_points = function(sig.locs, point) {
text(pos.pNew[, 1][sig.locs], (pos.pNew[, 2][sig.locs])+0.25,
labels = point, col = pch.col, cex = pch.cex,
lwd = 2)
然后点击“保存”按钮。
library(corrplot)
#> corrplot 0.90 loaded
#change the corrplot function as described above
trace(corrplot, edit=TRUE)
#> Tracing function "corrplot" in package "corrplot"
#> [1] "corrplot"
M<-cor(mtcars)
res1 <- cor.mtest(mtcars, conf.level = .95)
corrplot(cor(mtcars),
method="square",
type="lower",
p.mat = res1$p,
insig = "label_sig",
sig.level = c(.001, .01, .05),
pch.cex = 0.8,
pch.col = "yellow",
tl.col="black",
tl.cex=1,
addCoef.col = "black",
tl.pos="n",
outline=TRUE)
由 reprex 包于 2021 年 10 月 13 日创建(v2.0.1)
您只需将选项
addCoef.col = "black"
添加到 corrplot
为了解决星星的颜色冲突,我采用了这种方法,使更大的星星具有白色。我将其与以下颜色和布局一起使用。我无法避免重叠,但它对于我来说足够清晰:
cex.before <- par("cex")
par(cex = 0.7)
col <- colorRampPalette(c("#BB4444", "#EE9988", "#FFFFFF", "#77AADD", "#4477AA"))
corrplot::corrplot(cor(mtcars),
method="color",
col=col(200),
type="lower",
# Combine with significance
p.mat = res1$p,
insig = "label_sig",
sig.level = c(.001, .01, .05),
pch.cex = 3, # Increase size of stars
pch.col = "white", # Colour of stars
# hide correlation coefficient on the principal diagonal
diag=FALSE,
addCoef.col = "black", # Add coefficient of correlation
tl.col="black", tl.srt=45, #Text label color and rotation
tl.cex = 1/par("cex"), cl.cex = 1/par("cex") #Reduce text size of coefficients
)
par(cex = cex.before)