devtools::install_github('nimble-dev/rcjit')
library(rcjit)

logistic_map <- function(start, scale, steps) {
    result <- start
    for (i in 1:steps) {
        result <- scale * result * (1.0 - result)
    }
    return(result)
}

jit_logistic_map <- jit(logistic_map)  # <---------- jit( )

print(logistic_map(0.1, 3.6, 1000000))
# 0.791767

print(jit_logistic_map(0.1, 3.6, 1000000))
# 0.791767

library(microbenchmark)
microbenchmark(jit_logistic_map(0.1, 3.6, 1000000),
                   logistic_map(0.1, 3.6, 1000000))
# Unit: milliseconds
#                              expr       min        lq      mean    median       uq       max neval
# jit_logistic_map(0.1, 3.6, 1e+06)  2.472324  2.473969  2.490519  2.476032  2.49078  2.890946   100
#     logistic_map(0.1, 3.6, 1e+06) 40.078393 40.120312 40.919318 40.298471 41.74336 47.068705   100

Rcjit is a thin wrapper library around NIMBLE to make NIMBLE's compiler infrastructure easy to use.

The rcjit jit() function handles only a subset of NIMBLE code, but it does try to handle simple R functions that "look like C++". For complete detail, check out the NIMBLE User Manual. Some features of NIMBLE are not yet avialable in rcjit, for example recursion or allowing one jitted function to use another; if you need these features immediately, try using NIMBLE directly.

This is an experimental interface and will be changing rapidly, but we'd love your feedback and feature requests.

NIMBLE is an R package for programming with BUGS models. Some probabilistic programming languages perform black-box inference on user-defined models. NIMBLE provides more flexibility and lets users additionally define algorithms against models: inference algorithms, experimental design algorithms, basically anything that uses a graphical model as basic concept. To make NIMBLE algorithms fast, the authors built a compiler from parts of R to C++. You can read details in :

"Programming with models: writing statistical algorithms for general model structures with NIMBLE"
Perry de Valpine, Daniel Turek, Christopher J. Paciorek, Clifford Anderson-Bergman, Duncan Temple Lang, Rastislav Bodik
https://arxiv.org/pdf/1505.05093.pdf