Combining R with Java for Data Analysis

Java is a general-purpose language and is not particularly well suited for performing statistical analysis. Special languages and software environments have been created by and for statisticians to use. Statisticians think about programming and data analysis much different from Java programmers. These languages and tools make it easy to perform very sophisticated analyses on large data sets easily. Tools, such as R and SAS, contain a large toolbox of statistical tools that are well tested, documented and validated. For data analysis you want to use these tools.
In this session we will provide an overview of how to leverage the power of R from Java. R is the leading open source statistical package/language/environment. The first part of the presentation will provide an overview of R focusing on the differences between R and Java at the language level. We’ll also look at some of the basic and more advanced tests to illustrate the power of R. The second half of the presentation will cover how to integrate R and Java using rJava. We’ll look at leverage R from the new Java EE Batching (JSR 352) to provide robust statistical analysis for enterprise applications.


Authors:
Ryan Cuprak
undefined

Elsa Cuprak
Elsa was a statistician for the Cardiology/Heart Failure and Transplant Departments at Yale School of Medicine. She is an expert in statistics as well as SAS and Excel. Elsa has a masters degree in Actuary Science from the University of Iowa and bachelors in statistics from the University of California Berkley. She worked for several years as an actuary at both Met Life and the West Coast Life Insurance Company.