Numeric Computation and Statistical Data Analysis on the Java Platform

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language.

The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages.

Numeric Computation and Statistical Data Analysis on the Java Platform is a great choice for those who want to learn how statistical data analysis can be done using popular programming languages, who want to integrate data analysis algorithms in full-scale applications, and deploy such calculations on the web pages or computational servers regardless oftheir operating system. It is an excellent reference for scientific computations tosolve real-world problems using a comprehensive stack of open-source Java libraries included in the DataMelt (DMelt) project andwill be appreciated by many data-analysis scientists, engineers and students.

S. Chekanov was born in Minsk (Belarus) and received his Ph.D. inexperimental physics at Radboud University Nijmegen, The Netherlands. He hasmore than twenty five years of experience in high-energy particle physicsincluding advanced programming and analysis of large data volumes collected byhigh-energy experiments operated by major international collaborations. He haswritten a book and over a hundredprofessional articles, many of them based on analysis of experimental data fromlarge-scale international experiments, such as LEP (CERN, European Organizationfor Nuclear Research), HERA (DESY, German Electron Synchrotron) and LHC, theLarge Hadron Collider experiment at CERN. Over the past decade he has dividedhis time between data analysis, developing analysis tools and providingsoftware support for the Midwest data-analysis centre (USA) of the LHCexperiment. He is founder of thejWork.ORG community portal for promotingscientific computing for science and education. In 2005 he created a data-analysissoftware environment, which is presently known as DMelt.

Currently, this software is the world's leading open-source program fordata analysis, statistics and scientific visualization, incorporating Javapackages from more than 100 developers around the world and with thousands ofusers. Presently, he works at the Argonne National Laboratory (Chicago, USA).