Parallel Nonparametric Kernel Smoothing Methods for Mixed Data Types Using 'MPI'.

npRmpi

This is the R package npRmpi (Parallel Nonparametric Kernel Methods for Mixed Datatypes) written and maintained by Jeffrey S. Racine ([email protected]) and co-authored by Tristen Hayfield ([email protected]).

Installation

Presuming that a working implementation of MPI exists on the target machine, you can install the stable version on CRAN:

install.packages('npRmpi', dependencies = TRUE)

Or download the zip ball or tar ball, decompress and run R CMD INSTALL on it, or use the devtools package to install the development version:

library(devtools); install_github('JeffreyRacine/R-Package-np', ref = 'npRmpi')

Note also that if you wish a fast install without the building of vignettes (or if you do not have TeX installed on your system), add the option build_vignettes=FALSE to the install_github() call.

MPI (MPICH via MacPorts) Quick Setup

export RMPI_TYPE=MPICH
export RMPI_INCLUDE=/opt/local/include/mpich-mp
export RMPI_LIB_PATH=/opt/local/lib/mpich-mp
export RMPI_LIBS="-L/opt/local/lib/mpich-mp -lmpi"
export CC=mpicc
export CXX=mpicxx

Then build/install from the repo:

R CMD build .
R CMD INSTALL npRmpi_0.60-20.tar.gz

See BUILD.md and WORKTREES.md in this repo for local build details.

For more information on this project please visit the maintainer's website (https://experts.mcmaster.ca/people/racinej).