Kategori: R Programming

Reproducibility is a critical component of data science. In fact, it’s critical to all research—witness the reproducibility crisis currently engulfing academic research. It equally important in software development. We all expect our applications to work the same way…time after time. Software that operates erratically is undesirable. The unyielding regularly with which computers perform tasks could […]

Part 2: Parallel Processing with Microsoft R Server and MPI In Part 1 we saw how to configure a server with Microsoft R Server to make use of the Rmpi library to achieve parallel processing. In Part 2, we will look at how to launch R Server processes on multiple machines creating a flexible R […]

Part I: Setting Up the System In several previous blogs, we have talked about installing Microsoft R Server as a part of a SQL Server 2016 installation, and we have called attention to the fact that the SQL Server 2016 installation disk provides for a standalone installation of R Server. What we have not discussed […]

R Markdown is a formatting syntax that makes it easy to create dynamic reports. It’s based on the popular Markdown lightweight markup language for web writing. Markdown Markdown is a response to the growing importance of writing for on-line publication. Tools based around the concept of a printed page (e.g. Word, Google Docs) make little […]

Shiny is a web application framework for the R statistical computing language. It allows interactive applications to be written entirely in R. While it’s possible to write a general purpose web application using R and Shiny, it’s not the sweet spot of the framework. There are better general purpose web application frameworks—such as ASP.NET MVC. […]