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Java and Computing for Robust Statistics

In: Developments in Robust Statistics

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  • V. Todorov

    (Ericsson Austria AG)

Abstract

Summary The recent advances in the Java technology provoked increasing interest in using Java as a programming language for development of numerical software. Given its attractive language features it worths investigating the possibilities of writing software for robust computing in Java. In this paper the design and implementation of an object-oriented library for computing of high breakdown point robust multivariate location and covariance matrix estimates called JMCD is presented and its performance as compared to the corresponding FORTRAN implementations is examined. The FAST-MCD algorithm of Rousseeuw and Van Driessen (1999) written in Java can be competitive to FORTRAN (on PC/Windows platforms). The Java implementation is on average 30% slower with its efficiency depending on the size of the problem, but this could be accepted given the other advantages of the language.

Suggested Citation

  • V. Todorov, 2003. "Java and Computing for Robust Statistics," Springer Books, in: Rudolf Dutter & Peter Filzmoser & Ursula Gather & Peter J. Rousseeuw (ed.), Developments in Robust Statistics, pages 404-416, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-57338-5_35
    DOI: 10.1007/978-3-642-57338-5_35
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