Content area
Full text
SUMMARY
This article reviews Scilab, a free MATLAB-like programming system. Scilab can be used for data analysis and applied numerical work in both research and teaching. Scilab is an interesting alternative to some commercial programming environments. Copyright (c) 2001 John Wiley & Sons, Ltd.
1. INTRODUCTION
Scilab is a general-purpose programming environment that is similar to Matlab, Gauss and Octave, which were described in Anderson (1992), Rust (1993), Cribari-Neto (1997) and Cribari-Neto and Jensen (1997). Its core consists of a high-level matrix programming language, an interpreter, and a fairly standard set of numerical functions. Scilab has built-in support for linear algebra (customized LAPACK), linear programming, constrained quadratic and non-linear programming, data exchange with Matlab, optimal control and signal processing. Scilab can produce publication quality graphics and animated graphics. It can perform symbolic computations by interfacing with Maple. In addition to the built-in functions there are a few packages, written by Scilab users, that are available free of charge from the Internet.
Scilab has been developed at INRIA (Unite de recherche de Rocquencourt-Rocquencourt-BP. 105-78153 Le Chesnay Cedex (France), home page at www-rocq.inria.fr/scilab/). The source code and precompiled binaries can be downloaded free of charge from their web site. Unlike Octave, Scilab is not licensed under the GNU General Public License (GPL). INRIA holds the copyrights, but it allows users to distribute and modify the source code provided that they notify the authors and clearly state the original source of the software. INRIA does not provide commercial support for Scilab, but online documentation and bulletin boards exist and contain enough information for beginners as well as for advanced users.
I found that the main strengths of Scilab are its price and availability of its source code, free additional packages available on the Internet, the ability to easily extend the system with Scilab, C and FORTRAN libraries, precision and robustness. Scilab's main weaknesses are its unclear future development path, slow linear algebra routines, and lack of several standard econometric procedures.
1.1. Supported Hardware and Software Platforms
The last stable version, which is the one reviewed here, is version 2.5. It was released in December 1999. INRIA does not officially state any commitment to future development, but bug fixes and new functions are regularly posted on the Internet....