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Journal of Statistical Software - University of California at Los Angeles | 2024 Impact Factor:5.8 | Cite Score:12.3 | Q1

Journal of Statistical Software - University of California at Los Angeles - Impact Factor

Impact Factor and Journal Rank of Journal of Statistical Software

  • About: Journal of Statistical Software is a peer-reviewed journal published by the University of California at Los Angeles (UCLA). It focuses on the development and dissemination of open-access software for statistical analysis and data science. The journal provides a platform for researchers, statisticians, and software developers to publish articles and software reviews that advance the field of statistical software development and promote reproducible research.
  • Objective: The primary objective of Journal of Statistical Software is to promote the use of open-access software tools for statistical analysis and data visualization. The journal aims to facilitate the exchange of ideas, algorithms, and methodologies among statisticians, data scientists, and software developers. By publishing high-quality software articles and reviews, the journal contributes to the advancement of statistical software development and the reproducibility of scientific research.
  • Interdisciplinary Focus: Journal of Statistical Software adopts an interdisciplinary approach, welcoming contributions from various fields related to statistics, data science, and computational science, including but not limited to, Biostatistics, Econometrics, Machine Learning, Data Mining, Bayesian Statistics, Spatial Statistics, Time Series Analysis, Psychometrics, Statistical Genetics and Social Sciences. This interdisciplinary perspective fosters collaboration and innovation in statistical software development, leading to the creation of open-access tools that address the diverse needs of researchers and practitioners.
  • Global Reach and Impact: With a broad international readership and authorship, Journal of Statistical Software has a global reach and impact. Its publications contribute to the dissemination of knowledge and advancements in statistical software worldwide. The journal content influences both academic research and practical applications, driving progress in areas such as data analysis, visualization, and reproducible research.
  • High Standards and Rigorous Review: Maintaining high academic standards, Journal of Statistical Software conducts a rigorous peer-review process. Each submitted software article or review undergoes thorough evaluation by experts in the field to ensure the quality, usability, and scientific significance of the software. This stringent review process upholds the integrity and reputation of the journal, ensuring that only high-quality and impactful software tools are published.
  • Significance: Journal of Statistical Software plays a significant role in advancing research and practice in statistical software development and data science. By providing a platform for the publication and dissemination of open-access software tools, the journal contributes to the democratization of statistical analysis and promotes reproducible research practices. It serves as an essential resource for researchers, educators, and practitioners seeking to leverage open-access software tools to conduct rigorous and transparent statistical analysis and data visualization.

  • Editor-in-Chief:  Bettina Grün

  • Scope: The Journal of Statistical Software (JSS) is a renowned peer-reviewed academic journal dedicated to the publication of software tools and algorithms for statistical analysis. It provides a platform for researchers, developers, and practitioners to share innovative software packages, libraries, and methodologies that advance the field of statistics. Here is an overview of its key focus areas and scope:
  • 1. Statistical Software Packages:
    Publication of new software packages and libraries designed for statistical analysis, data visualization, and data manipulation.
    Coverage of popular statistical software environments such as R, Python, MATLAB, and SAS.
  • 2. Algorithms and Methods:
    Description and implementation of novel algorithms and statistical methods for data analysis, modeling, and inference.
    Coverage of machine learning algorithms, Bayesian methods, time series analysis techniques, and more.
  • 3. Data Visualization and Graphics:
    Development of tools and techniques for creating informative and visually appealing graphics and plots to explore and communicate data.
    Coverage of interactive visualization tools, geospatial visualization, and advanced plotting libraries.
  • 4. Reproducible Research:
    Promotion of reproducible research practices through the publication of software papers with open-source code and data.
    Coverage of literate programming tools, version control systems, and workflow management techniques.
  • 5. Computational Statistics:
    Innovative applications of statistical computing techniques to solve complex real-world problems in various domains.
    Coverage of statistical modeling, simulation methods, optimization algorithms, and parallel computing.
  • Latest Research Topics for PhD in Computer Science
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  • Print ISSN:  15487660

    Electronic ISSN:  

  • Abstracting and Indexing:  Scopus, Science Citation Index Expanded

  • Imapct Factor 2024:  5.8

  • Subject Area and Category:  Computer Science,Software,Decision Sciences Statistics, Probability and Uncertainty,Mathematics,Statistics and Probability

  • Publication Frequency:  

  • H Index:  187

  • Best Quartile:

    Q1:  Software

    Q2:  

    Q3:  

    Q4:  

  • Cite Score:  12.3

  • SNIP:  4.608

  • Journal Rank(SJR):  3.211