by Thomas Dinsmore On April 26, SAS published on its website an undated Technical Paper entitled Big Data Analytics: Benchmarking SAS, R and Mahout. In the paper, the authors (Allison J. Ames, Ralph Abbey and Wayne Thompson) describe a recent project to compare model quality, product completeness and ease of use for two SAS products together with open source...
Blog Archives
SAS Big Data Analytics Benchmark (Part One)
by Thomas Dinsmore On April 26, SAS published on its website an undated Technical Paper entitled Big Data Analytics: Benchmarking SAS, R and Mahout. In the paper, the authors (Allison J. Ames, Ralph Abbey and Wayne Thompson) describe a recent project to compare model quality, product completeness and ease of use for two SAS products together with open source...
Announcing Revolution R Enterprise 6.2
We are pleased to announce that Revolution R Enterprise Release 6.2 is available to new subscribers today. This new software release from Revolution Analytics includes a number of key new features: Support for open source R 2.15.3, the latest stable release of R. Since Release 2.14.2, the R Project has added 89 new features, 11 performance enhancements and 139...
Looking Ahead: Revolution R Enterprise Release 7
by Thomas Dinsmore Revolution R Enterprise Release 6.2 goes live next week, so naturally our development team is thinking ahead to Release 7, which we plan to release later this year. Some of those enhancements are hush-hush, and we can't talk about them yet. But one of the most important enhancements we've already announced: support for predictive analytics inside...
What’s New in Release 6.2: Additional ScaleR Features
by Thomas Dinsmore Revolution R Enterprise Release 6.2 is in track for General Availability on April 22. In previous posts, I've commented on support for open source R 2.15.3 and Stepwise Regression. Today I'll wrap this series with a summary of some of the other new features supported in this release. Parallel Random Number Generation For analysts seeking to...
What’s New in 6.2: Stepwise Regression for Big Data
by Thomas Dinsmore This is the third in a series of posts highlighting new features in Revolution R Enterprise Release 6.2, which is scheduled for General Availability April 22. This week's post features our new Stepwise Regression capability. The Stepwise process starts with a specified model and then sequentially adds into or removes from the model the variable that...
What’s New in 6.2: Open Source R 2.15.3
by Thomas Dinsmore Last week, Revolution Analytics released the Limited Availability edition of Revolution R Enterprise Release 6.2. Interest in this new release is high, and we're very pleased with user response. Over the next several weeks, I will share more detailed information about the capabilities included in this new release. Revolution R Enterprise Release 6.2 supports open source...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
