update readme with more details about OS X installation

README.md

@@ -60,17 +60,30 @@ It is recommended to:
 
 1. Use high-performance BLAS (such as OpenBLAS, MKL, Apple Accelerate).
 1. Add proper compiler optimizations in your `~/.R/Makevars`. For example on recent processors (with AVX support) and compiler with OpenMP support, the following lines could be a good option:
-    ```txt
-    CXX11FLAGS += -O3 -march=native -fopenmp
-    CXXFLAGS   += -O3 -march=native -fopenmp
-    ```
 
-If you are on **Mac** follow the instructions [here](https://github.com/coatless/r-macos-rtools). After installation of `clang4`, additionally put a `PKG_CXXFLAGS += -DARMA_USE_OPENMP` line in your `~/.R/Makevars`. After that, install `rsparse` in the usual way.
+```
+CXX11FLAGS += -O3 -march=native -fopenmp
+CXXFLAGS   += -O3 -march=native -fopenmp
+```
+
+### Mac OS
+
+If you are on **Mac** follow the instructions at [https://mac.r-project.org/openmp/](https://mac.r-project.org/openmp/). After `clang` configuration, additionally put a `PKG_CXXFLAGS += -DARMA_USE_OPENMP` line in your `~/.R/Makevars`. After that, install `rsparse` in the usual way. 
+
+Also we recommend to use [vecLib](https://developer.apple.com/documentation/accelerate/veclib) - Apple’s implementations of BLAS.
+
+```sh
+ln -sf  /System/Library/Frameworks/Accelerate.framework/Frameworks/vecLib.framework/Versions/Current/libBLAS.dylib /Library/Frameworks/R.framework/Resources/lib/libRblas.dylib
+```
+
+### Linux
 
 On Linux, it's enough to just create this file if it doesn't exist (`~/.R/Makevars`).
 
 If using OpenBLAS, it is highly recommended to use the `openmp` variant rather than the `pthreads` variant. On Linux, it is usually available as a separate package in typical distribution package managers (e.g. for Debian, it can be obtained by installing `libopenblas-openmp-dev`, which is not the default version), and if there are multiple BLASes installed, can be set as the default through the [Debian alternatives system](https://wiki.debian.org/DebianScience/LinearAlgebraLibraries) - which can also be used [for MKL](https://stackoverflow.com/a/49842944/5941695).
 
+### Windows
+
 By default, R for Windows comes with unoptimized BLAS and LAPACK libraries, and `rsparse` will prefer using Armadillo's replacements instead. In order to use BLAS, **install `rsparse` from source** (not from CRAN), removing the option `-DARMA_DONT_USE_BLAS` from `src/Makevars.win` and ideally adding `-march=native` (under `PKG_CXXFLAGS`). See [this tutorial](https://github.com/david-cortes/R-openblas-in-windows) for instructions on getting R for Windows to use OpenBLAS. Alternatively, Microsoft's MRAN distribution for Windows comes with MKL.
 
 # Materials