There are some problems which are just to slow when run in R directly, and one has to resort to lower level languages.

Using C++

inline, in conjunction with Rcpp, provides support for embedding C++ code, which may make for somewhat easier coding.

library(Rcpp, warn.conflicts=FALSE)

cppFunction('NumericVector rowSumsC(NumericMatrix x) {
  int nrow = x.nrow(), ncol = x.ncol();
  NumericVector out(nrow);

  for (int i = 0; i < nrow; i++) {
    double total = 0;
    for (int j = 0; j < ncol; j++) {
      total += x(i, j);
    out[i] = total;
  return out;

x <- matrix(sample(100), 10)
##  [1] 458 558 488 458 536 537 488 491 508 528

Notice that this time the function rowSumsC() is fully declared in the string (not just its body), and that cppFunction() creates an R function of the same name that we can call.

Such functions are likely to be faster than careful R equivalents, and also competitive with stripped-down versions.

               .rowSums(x, 10, 10),
## Unit: microseconds
##                 expr   min    lq median    uq    max neval
##          rowSumsC(x) 2.568 3.001  3.641 3.827 10.754   100
##           rowSums(x) 6.343 7.018  7.771 8.210 31.146   100
##  .rowSums(x, 10, 10) 1.191 1.530  1.639 1.845  4.474   100

Calling C Code

Using inline

The inline package also allows you to embed C functions directly into your R code, and will compile them for you. The details are complicated.

Here’s a simple example taken from Hadley Wickham’s Advanced R wiki.

add <- cfunction(sig = c(a = "integer", b = "integer"),
  body = "
  SEXP result = PROTECT(allocVector(REALSXP, 1));
  REAL(result)[0] = asReal(a) + asReal(b);

  return result;
add(1, 5)
## [1] 6

The main arguments are body, a string which gives the body of the C function, and sig, which gives its argument signature.


Objects of class SEXP are R objects (S expressions). There are various convenience functions for editing them. The most useful types are:

  • REALSXP: numeric vector
  • INTSXP: integer vector
  • LGLSXP: logical vector
  • STRSXP: character vector
  • VECSXP: list


R’s automatic garbage collection may attempt to delete R objects unless we prevent it from doing so; this is the purpose of the PROTECT() commands in the C code. Calling PROTECT() adds the object onto a protected stack, and UNPROTECT(1) removes one (i.e.
the most recent) protected item from the stack. You should unprotect all objects before returning.