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A Survey of Open Source Statistical Software (OSSS) and Their Data Processing Functionalities

A Survey of Open Source Statistical Software (OSSS) and Their Data Processing Functionalities

Gao Niu, Richard S. Segall, Zichen Zhao, Zhijian Wu
Copyright: © 2021 |Volume: 12 |Issue: 1 |Pages: 20
ISSN: 1942-3926|EISSN: 1942-3934|EISBN13: 9781799860600|DOI: 10.4018/IJOSSP.2021010101
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MLA

Niu, Gao, et al. "A Survey of Open Source Statistical Software (OSSS) and Their Data Processing Functionalities." IJOSSP vol.12, no.1 2021: pp.1-20. http://doi.org/10.4018/IJOSSP.2021010101

APA

Niu, G., Segall, R. S., Zhao, Z., & Wu, Z. (2021). A Survey of Open Source Statistical Software (OSSS) and Their Data Processing Functionalities. International Journal of Open Source Software and Processes (IJOSSP), 12(1), 1-20. http://doi.org/10.4018/IJOSSP.2021010101

Chicago

Niu, Gao, et al. "A Survey of Open Source Statistical Software (OSSS) and Their Data Processing Functionalities," International Journal of Open Source Software and Processes (IJOSSP) 12, no.1: 1-20. http://doi.org/10.4018/IJOSSP.2021010101

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Abstract

This paper discusses the definitions of open source software, free software and freeware, and the concept of big data. The authors then introduce R and Python as the two most popular open source statistical software (OSSS). Additional OSSS, such as JASP, PSPP, GRETL, SOFA Statistics, Octave, KNIME, and Scilab, are also introduced in this paper with function descriptions and modeling examples. They further discuss OSSS's capability in artificial intelligence application and modeling and Popular OSSS-based machine learning libraries and systems. The paper intends to provide a reference for readers to make proper selections of open source software when statistical analysis tasks are needed. In addition, working platform and selective numerical, descriptive and analysis examples are provided for each software. Readers could have a direct and in-depth understanding of each software and its functional highlights.