我想在R中绘制与此类似的直方图(如果可能,不安装其他库)。
图像应包含直方图,指示频率的标签,标准偏差曲线,平均线和指示标准偏差距离的线,例如+1,-1 SD处的红线,+ 2处的黄线,-2 SD和绿线为+ 3,-3 SD
这是绘制多个直方图的代码,但无法绘制标准偏差曲线。驾驶标准偏差的代码取自here。
library(xts)
dimension = function(df){
kk = dim(df)[2];
x = round(sqrt(kk),0);
y = ceiling(kk/x);
return(c(x,y))
}
set.seed(3)
Ex <- xts(1:100, Sys.Date()+1:100)
df = data.frame(Ex,matrix(rnorm(100*6,mean=123,sd=3), nrow=100))
df<-df[,-1]
m<-list()
std<-list()
par(mfrow = dimension(df))
for(i in names(df)){
m[[i]]<-mean(df[[i]],na.rm=TRUE)
std[[i]]<-sd(df[[i]],na.rm=TRUE)
hist(df[[i]] , main="Histogram",xlab="x",col="green",label=TRUE,plot = TRUE)
curve(dnorm(x, mean=m[[i]], sd=std[[i]]), col="darkblue", lwd=2, add=TRUE, yaxt="n")
}
答案 0 :(得分:1)
因此可以使用abline()
轻松添加标准偏差线。此外,正如Pascal建议的那样,使用freq = FALSE
来适当缩放y轴。
for(i in names(df)){
m[[i]]<-mean(df[[i]],na.rm=TRUE)
std[[i]]<-sd(df[[i]],na.rm=TRUE)
hist(df[[i]] , main="Histogram",xlab="x",col="green",label=TRUE,plot = TRUE, freq = F)
curve(dnorm(x, mean=m[[i]], sd=std[[i]]), col="darkblue", lwd=2, add=TRUE, yaxt="n")
# Use abline
abline(v = m[[i]], lty = 2)
abline(v = m[[i]]+std[[i]], lty = 2)
abline(v = m[[i]]-std[[i]], lty = 2)
abline(v = m[[i]]+2*std[[i]], lty = 2)
abline(v = m[[i]]-2*std[[i]], lty = 2)
}