You need to build a curve with a standard error in R

Question

I need to plot a curve with standard error as a shaded area. For example, I have a matrix like temporary bins:

Age CO2 Standard_error 0 1 1.42E-13 0.5 0.998268422989761 0.00169763164186241 1 0.995743963199747 0.00479900584235718 1.5 0.995062233834876 0.0103274581695151 2 1.00398569520812 0.0195262589284694 2.5 1.03116826950464 0.0329875314671063 3 1.07422916427453 0.049116358866183 3.5 1.11992125335082 0.0646007093291105 4 1.15670166266193 0.0770010287134558 4.5 1.18120894601468 0.0860204557092314 5 1.1972210240662 0.0930892044882256 5.5 1.21094781023761 0.0999899575457834 6 1.22407556599768 0.10698386874689 6.5 1.23264038072763 0.112706241640139 7 1.23471241147135 0.116401516372119 7.5 1.23341569261173 0.118772825620555 8 1.23279196992244 0.120901622556905 8.5 1.2346500417623 0.123408621016096 9 1.23831115917507 0.126316578608025 9.5 1.24201463025631 0.129312831831815 

And I would like to plot a curve with this estimated standard error. Most of the functions that I saw (in particular in ggplot2) evaluate the standard error, and I already rated this data. Any help is appreciated!

Answer 1

You can use ggplot2 in combination with geom_ribbon :

 library(ggplot2) ggplot(dat, aes(x = Age, y = CO2)) + geom_line() + geom_ribbon(aes(ymin = CO2 - Standard_error, ymax = CO2 + Standard_error), alpha = 0.2) 

Answer 2

?matplot often convenient for this kind of task when building the R base:

 matplot( dat$Age, dat$CO2 + outer(dat$Standard_error, c(0,1,-1)), type="l", lty=c(1,2,2), col=c(1,2,2), xlab="Age", ylab="CO2" ) 

If shading is critical, I'll move on to polygon :

 ses <- dat$CO2 + outer(dat$Standard_error, c(1,-1)) with(dat, plot( Age, CO2, type="l", ylim=range(ses), panel.first=polygon(c(Age,rev(Age)), c(ses[,1],rev(ses[,2])),border=NA, col="#ebebeb") ) )