```
library(demography)
library(latex2exp)
<- lca(fr.mort)
fit
par(mfrow=c(2,2), mar=c(4,5,2,1), family="serif")
plot(fit$age, fit$ax, type="l", ylab=TeX("a_x"), xlab="Age: x")
plot(fit$age, fit$bx, type="l", ylab=TeX("b_x"), xlab="Age: x")
plot(0, type="n", axes=FALSE, xlab="", ylab="")
text(1, 0, TeX("m_{x,t} = a_x + k_tb_x + e_{x,t}"))
plot(fit$kt, ylab=TeX("k_t"), xlab="Year: t")
```

# Mathematical annotations on R plots

I’ve always struggled with using `plotmath`

via the `expression`

function in R for adding mathematical notation to axes or legends. For some reason, the most obvious way to write something never seems to work for me and I end up using trial and error in a loop with far too many iterations.

So I am very happy to see the new **latex2exp** package available which translates LaTeX expressions into a form suitable for R graphs. This is going to save me time and frustration!

Here is a quick example showing a Lee-Carter decomposition of some mortality data.

There are several more examples in the package documentation.

The results are still a little ugly, but that is because of the limitations of base graphics in R. To get something more LaTeX-like, the **tikzDevice** package can be used as follows.

```
library(demography)
library(tikzDevice)
<- lca(fr.mort)
fit
tikz("tikz-test.tex",width=15/2.54,height=12/2.54)
par(mfrow=c(2,2),mar=c(4,5,2,1),family="serif")
plot(fit[["age"]],fit$ax,type="l",
ylab="$a_x$", xlab="Age: $x$")
plot(fit[["age"]],fit$bx,type="l",
ylab="$b_x$", xlab="Age: $x$")
plot(0,type="n",axes=FALSE,xlab="",ylab="")
text(1,0,"$m_{x,t} = a_x + k_tb_x + e_{x,t}$")
plot(fit$kt,ylab="$k_t$", xlab="Year: $t$")
dev.off()
```

While the results look much nicer, it is rather slow.