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This is an extension package to the R package grpSLOPE. It contains Monte Carlo based methods for the estimation of the regularizing sequence.

Essentially, this package contains only one function, lambdaMC. However it will automatically install the R package grpSLOPE as a dependency, which contains all the remaining functionality.

Installation

Your R configuration must allow for a working Rcpp. This is generally not a problem on Unix/Linux, but setting it up on Windows may require some work.

The easiest way to install the latest development version of grpSLOPEMC is by using the R package devtools. Just open up an R session and run:

# Install devtools, if you haven't already.
install.packages("devtools")

library(devtools)
install_github("agisga/grpSLOPEMC")

If you don't want to use devtools, you can install grpSLOPEMC by downloading the source code and then following these steps:

  1. Install the R packages Rcpp and RcppEigen if you don't have them installed already.
  2. Go to the directory that contains the grpSLOPEMC directory (which contains the grpSLOPEMC source code).
  3. Open an R session and run Rcpp::compileAttributes("./grpSLOPEMC"). Then quit R.
  4. Run R CMD build grpSLOPEMC. You should then have a file like grpSLOPEMC_0.1.0.tar.gz.
  5. Run R CMD INSTALL grpSLOPEMC_0.1.0.tar.gz to install the package.

Contributing

Code style

Variable names are all lower case with words separated by dots. Function names begin with a lower case letter and are written in camel case. Constants names are all caps. Otherwise, I try to follow Google's R style guide.

Workflow

  1. Modify the code.
  2. Open grpSLOPEMC.Rproj with RStudio.
  3. Run devtools::document().
  4. Do "Build and Reload" from the menu (or CTRL-Shift-B).
  5. Do devtools::test() to run the unit tests.
  6. Install with devtools::install()