I’m a bit obsessive with words. May be I should have used learning in the title, rather than teaching code. Or perhaps remembering code. You know? Code where one actually has very clear idea of what is going on; for example, let’s say that we are calculating the average of a bunch of n numbers, we can have a loop that will add up each of them and then divide the total by n. Of course we wouldn’t do that in R, but use a simple function: mean(x).
In a previous post I compared R and Julia code and one of the commenters (Andrés) rightly pointed out that the code was inefficient. It was possible to speed up the calculation many times (and he sent me the code to back it up), because we could reuse intermediate results, generate batches of random numbers, etc. However, if you have studied the genomic selection problem, the implementations in my post are a lot closer to the algorithm. It is easier to follow and to compare, but not too flash in the speed department; for the latter we’d move to production code, highly optimized but not very similar to the original explanation.
