Need to plot a curve with 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 this one, as time 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 the curve with this estimated standard error. Most of the functions I have seen (in particular within ggplot2) estimate the standard error, and I have these data already estimated. Any help is appreciated!

Answer 1

?matplot is often handy for this sort of task in base R plotting:

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 the shading is crucial, I'd turn 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")
  )
)

Answer 2

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)