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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.

 library(demography) library(latex2exp)   fit <- lca(fr.mort)   par(mfrow=c(2,2), mar=c(4,5,2,1), family="serif") plot(fit$age, fit$ax, type="l", ylab=latex2exp("a_x"), xlab="Age: x") plot(fit$age, fit$bx, type="l", ylab=latex2exp("b_x"), xlab="Age: x") plot(0, type="n", axes=FALSE, xlab="", ylab="") text(1, 0, latex2exp("m_{x,t} = a_x + k_tb_x + e_{x,t}")) plot(fit$kt, ylab=latex2exp("k_t"), xlab="Year: t") There are several more examples in the package documentation. The results are still a little ugly, but that is because of the limitations of base graphics in R. To get something more LaTeX-like, the tikzDevice package can be used as follows.  library(demography) library(tikzDevice) fit <- lca(fr.mort) tikz("tikz-test.tex",width=15/2.54,height=12/2.54) par(mfrow=c(2,2),mar=c(4,5,2,1),family="serif") plot(fit[["age"]],fit$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.