# R and C++

You are right here, if you have an R project which is not fast enough and following conditions are true. You checked for existing R libraries with good performance. Typically those would be libraries implemented in C++ with R wrappers. You checked your code for suboptimal passages and they cant be fixed within R. Then it is a good idea to use Rcpp to solve such problems as necessary loops, large recursive problems and need for advanced data structures not available in r. It makes sense to avoid a pure C++ project because we would not be able to use advantages of R.

# Related

- [notebook] Spatial image analysis in R
- [] Python and C++
- [] Introduction to R
- [] Octave and C++
- [] Introduction to C++
- [notebook] Mapreduce in R - Prime Numbers
- [slides] ML Introduction
- [slides] ML Programming Languages
- [notebook] Message Passing Interface - Prime Number Calculation
- [notebook] Extract Snippets from Images