The new R Journal is out! Click for a complete table of content with links to all papers.

LOYALTY PROGRAM CHOICE BASED ON DEPARTURE COUNT If you read Decision Science News, you’re probably a professor or grad student or researcher or policy type who flies around a lot to conferences, symposia, workshops, tutorials, summer schools, and all-hands meetings. You travel the globe to give talks and work with co-authors. All this flying around The post Which...

Lately, I have been working with finite mixture models for my postdoctoral work on data-driven automated gating. Given that I had barely scratched the surface with mixture models in the classroom, I am becoming increasingly comfortable with them. With this in mind, I wanted to explore their application to classification because there are times when a single class is clearly made up of...

Statistical software is normally used during the analysis stage of a project and a cleaned up static graphic is created for the presentation. If the presentation is in web format then there are some considerations that are needed. The trick is to find ways to implement those graphs in that web format so the graph

I’ve been enjoying working with Joe Cheng’s Shiny Server and wanted to create a quick step-by-step guide on installing it on an AWS CentOS EC2 instance as the standard Shiny Server instructions assume the typical dependencies are installed: 1. Shiny’s instructions say to install libssl-dev (sudo yum install libssl-dev), here is the CentOS equivalent : sudo yum install openssl-devel

PCA is a very common method for exploration and reduction of high-dimensional data. It works by making linear combinations of the variables that are orthogonal, and is thus a way to change basis to better see patterns in data. You either do spectral decomposition of the correlation matrix or singular value decomposition of the data

Introduction A few first posts of this blog will demonstrate how to build each report hosted by the business intelligence (BI) application dashboard shown below (see Fig. 1). This application uses the following tools and technologies R – a free software environment for statistical computing and graphics, ASP.NET MVC4 – a free framework for building

e-mails with the latest R posts.

(You will not see this message again.)