问题
Say I some data, d
, and I fit nls models to two subsets of the data.
x<- seq(0,4,0.1)
y1<- (x*2 / (0.2 + x))
y1<- y1+rnorm(length(y1),0,0.2)
y2<- (x*3 / (0.2 + x))
y2<- y2+rnorm(length(y2),0,0.4)
d<-data.frame(x,y1,y2)
m.y1<-nls(y1~v*x/(k+x),start=list(v=1.9,k=0.19),data=d)
m.y2<-nls(y2~v*x/(k+x),start=list(v=2.9,k=0.19),data=d)
I then want to plot the fitted model regression line over data, and shade the prediction interval. I can do this with the package investr
and get nice plots for each subset individually:
require(investr)
plotFit(m.y1,interval="prediction",ylim=c(0,3.5),pch=19,col.pred='light blue',shade=T)
plotFit(m.y2,interval="prediction",ylim=c(0,3.5),pch=19,col.pred='pink',shade=T)
However, if I plot them together I have a problem. The shading of the second plot covers the points and shading of the first plot:
1: How can I make sure the points on the first plot end up on top of the shading of the second plot?
2: How can I make the region where the shaded prediction intervals overlap a new color (like purple, or any fusion of the two colors that are overlapping)?
回答1:
Use adjustcolor
to add transparency like this:
plotFit(m.y1, interval = "prediction", ylim = c(0,3.5), pch = 19,
col.pred = adjustcolor("lightblue", 0.5), shade = TRUE)
par(new = TRUE)
plotFit(m.y2, interval = "prediction", ylim = c(0,3.5), pch = 19,
col.pred = adjustcolor("light pink", 0.5), shade = TRUE)
Depending on what you want you can play around with the two transparency values (here both set to 0.5) and possibly make only one of them transparent.
来源:https://stackoverflow.com/questions/33305620/plotting-nls-fits-with-overlapping-prediction-intervals-in-a-single-figure