On 13/11/2014, at 3:52 pm, Brandon Allbery
It is an open source implementation of S ( http://en.wikipedia.org/wiki/S_(programming_language) ) which was developed specifically for statistical applications. I would wonder how much of *that* was shaped by Fortran statistical packages….
The prehistoric version of S *was* a Fortran statistical package. While the inventors of S were familiar with GLIM, GENSTAT, SPSS, SAS, BMDP, MINITAB, &c. they _were_ at Bell Labs, and so the language looks a lot like C. Indeed, several aspects of S were shaped by UNIX, in particular the way S (but not R) treats the current directory as an “outer block”. Many (even new) R packages are wrappers around Fortran code. However, that has had almost no influence on the language itself. In particular: - arrays are immutable
(v <- 1:5) w <- v w[3] <- 33 w [1] 1 2 33 4 5 v [1] 1 2 3 4 5
- functions are first class values and higher order functions are commonplace - function arguments are evaluated lazily - good style does *NOT* “traverse arrays by indexes” but operates on whole arrays in APL/Fortran 90 style. For example, you do not do for (i in 1:m) for (j in 1:n) r[i,j] <- f(v[i], w[j]) but r <- outer(v, w, f) If you _do_ “express data transformations and queries functionally in R” — which I repeat is native good style — it will perform well; if you “traverse arrays by indexes” you will wish you hadn’t. This is not something that Fortran 66 or Fortran 77 would have taught anyone. Let me put it this way: R is about as close to a functional language as you can get without actually being one. (The implementors of R consciously adopted implementation techniques from Scheme.)