[This article was first published on EvolvingSpaces, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
I know know…I’ve been away again…Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
We (myself and Mark Lake) are presenting a paper at the CECD conference and we have still some to stuff to finish…so I’m really, really busy… I’ll post asap a much more detailed post on the conference and on our paper, but before that I just wanted to share an useful link I found this morning which would have been handy a couple of month ago.
As I said, I’m writing my ABM in R this time. There are many good reasons (but also bad reasons) for this which I’m gonna write on another post (yes I keep promising…). Having said that, R is terribly slow. Yes you can write things in C and call them inside your function, but the main reason is that it is terribly bad on looping. And an ABM involves a lot of looping. Then I realised that many people avoid using loops in R, and instead use the series of “apply” function. These are however hard to grasp, but this blog explains it very elegantly. I wish I had read this long ago…Anyway, when you master the “apply” family, you can also play around with the mcapply() function of the multicore package which parallels the apply function through your cores, fastening alot your simulation!
To leave a comment for the author, please follow the link and comment on their blog: EvolvingSpaces.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.