The oem package for penalized regression is on CRAN
The oem package has been on CRAN for some time now, but with the latest update I expect few structural changes to the user interface.
oem is a package for the estimation of various penalized regression models using the oem algorithm of Xiong et al. (2016). The focus of
oem is to provide high performance computation for big tall data. Many applications not only have a large number of variables, but a vast number of observations;
oem is designed to perform well in these settings.
Fast and Big Linear Model Fitting with bigmemory and RcppEigen
In a previous post, I went over the basics of linking up bigmemory and the eigen C++ library via RcppEigen. In this post I’ll take this a bit further by creating a version of the
fastLm() function of RcppEigen that can accept bigmemory objects. By doing so, we will create a fast way to fit linear models using data which is too big to fit in RAM. With RcppEigen, fitting linear models using out-of-memory computation doesn’t have to be slow. The code for this is all on github in the bigFastlm package.
Linking bigmemory and RcppEigen
The bigmemory package offers a set of tools for R which allow for manipulation larger-than-memory objects within R. It has some basic functions but is certainly not comprehensive. The eigen C++ linear algebra library is a highly efficient numerical linear algebra library and can be interfaced to R through RcppEigen by Douglas Bates and Dirk Eddelbuettel. If bigmemory and Eigen can be linked, then one would be able to do highly efficient linear algebra computation on data that is too big for memory (exactly what you thought R couldn’t do).Read More
rfunctions Package on Github
This post is mostly an attempt to familiarize myself with Rmarkdown, jekyll, and github. I recently posted an R package (rfunctions), which contains some functions I wrote (or modified) that make my life a little easier. I’ll go through some examples in R to highlight the various functions included.Read More