JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS

Scope & Guideline

Exploring the intersection of computation and graphical representation.

Introduction

Immerse yourself in the scholarly insights of JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN1061-8600
PublisherTAYLOR & FRANCIS INC
Support Open AccessNo
CountryUnited Kingdom
TypeJournal
Convergefrom 1992 to 2024
AbbreviationJ COMPUT GRAPH STAT / J. Comput. Graph. Stat.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106

Aims and Scopes

The Journal of Computational and Graphical Statistics focuses on advancing the field of statistics through computational methods and graphical techniques. It aims to bridge the gap between theoretical statistical methodologies and practical applications, facilitating innovations in the analysis, visualization, and interpretation of complex data.
  1. Computational Statistics:
    Emphasizing the development and application of statistical methods that leverage computational techniques, including Monte Carlo methods, Bayesian inference, and machine learning algorithms.
  2. Graphical Methods:
    Focusing on the use of graphical representations to enhance understanding and communication of statistical results, including visualization techniques for high-dimensional data.
  3. Bayesian Analysis:
    Concentrating on Bayesian methodologies, including Bayesian modeling, inference, and computational techniques that support Bayesian statistics.
  4. High-Dimensional Data Analysis:
    Addressing challenges and methodologies related to the analysis of high-dimensional datasets, including variable selection, dimension reduction, and regularization techniques.
  5. Functional Data Analysis:
    Exploring statistical methods for analyzing data that can be represented as functions, such as time series and curves.
  6. Multivariate and Spatial Statistics:
    Investigating statistical methods for multivariate data and spatial processes, including hierarchical models and spatially correlated data.
The Journal of Computational and Graphical Statistics has been responsive to the evolving landscape of data analysis, with emerging themes reflecting current trends and innovations in statistical methodologies.
  1. Machine Learning Integration:
    There is a growing trend towards integrating machine learning techniques with traditional statistical methods, as evidenced by an increase in papers that explore hybrid methodologies.
  2. Nonparametric and Robust Methods:
    An emerging focus on nonparametric methods and robust statistics is apparent, particularly in the context of handling high-dimensional and complex datasets.
  3. Dynamic and Time-Varying Models:
    Research on dynamic models and time-varying processes is gaining momentum, reflecting the need to analyze data that evolves over time.
  4. Graphical Models and Network Analysis:
    Increased interest in graphical models, particularly in the context of network analysis, indicates a trend towards understanding complex relationships in data.
  5. Advanced Bayesian Techniques:
    The development of advanced Bayesian techniques, including variational inference and hierarchical modeling, signifies a robust interest in enhancing Bayesian methodologies.
  6. Functional and Longitudinal Data Analysis:
    The focus on functional data and longitudinal data analysis is expanding, with innovative approaches to modeling and inference in these areas.

Declining or Waning

While the journal has consistently published a wide array of topics, certain themes appear to be gradually losing prominence. This decline may reflect shifts in the research landscape or evolving interests within the field.
  1. Traditional Parametric Models:
    There is a noticeable decline in papers focusing solely on traditional parametric statistical models, as researchers increasingly explore nonparametric and flexible modeling approaches.
  2. Non-Bayesian Methods:
    The journal has seen a decrease in the publication of non-Bayesian statistical methods, as Bayesian approaches continue to dominate the field.
  3. Basic Statistical Techniques:
    The frequency of papers discussing fundamental statistical techniques appears to be waning, with a shift towards more complex methodologies that address contemporary data challenges.
  4. Classical Hypothesis Testing:
    Classical hypothesis testing methods are appearing less frequently, as newer approaches that incorporate Bayesian principles and machine learning gain traction.
  5. Simple Visualization Techniques:
    Basic visualization techniques are being overshadowed by more sophisticated graphical methods that integrate data science and machine learning.

Similar Journals

Wiley Interdisciplinary Reviews-Computational Statistics

Pioneering Innovative Solutions in Statistical Applications
Publisher: WILEYISSN: 1939-0068Frequency: 6 issues/year

Wiley Interdisciplinary Reviews: Computational Statistics is a leading journal published by WILEY, renowned for its influential contributions to the field of statistics and its application in computational studies. With an impressive impact factor reflected in its 2023 categorization as Q1 in Statistics and Probability, this journal ranks among the top in its category, positioned at 20 out of 278 in Scopus, placing it in the 92nd percentile for its discipline. The journal spans from 2009 to 2024 and offers a rich repository of interdisciplinary insights that encompass both theoretical advancements and practical applications of computational statistics, making it an invaluable resource for researchers, professionals, and students alike. While it does not currently offer open access, the journal's commitment to high-quality, peer-reviewed content ensures that it remains a trusted source for cutting-edge developments and methodologies in the rapidly evolving realm of computational statistics.

JIRSS-Journal of the Iranian Statistical Society

Connecting Researchers to the Pulse of Statistical Innovation.
Publisher: IRANIAN STATISTICAL SOCISSN: 1726-4057Frequency: 2 issues/year

JIRSS - Journal of the Iranian Statistical Society is a prominent academic journal dedicated to the field of statistics and probability, published by the esteemed Iranian Statistical Society. With its ISSN number 1726-4057 and E-ISSN 2538-189X, this journal serves as a vital platform for disseminating cutting-edge research and advancements in statistical methodology and its applications. Established in 2011, JIRSS has consistently contributed to the academic community, achieving a 2023 Scopus rank of #180 out of 278 in its category, placing it within the 35th percentile in the dynamic domain of Mathematics: Statistics and Probability. As an Open Access publication, it enhances accessibility for researchers, professionals, and students, facilitating a wider engagement with innovative statistical techniques and theories. The journal aims to foster collaboration and knowledge exchange among statisticians, ultimately enriching the field and its impact on various scientific disciplines.

CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE

Advancing Statistical Knowledge Since 1973
Publisher: WILEYISSN: 0319-5724Frequency: 4 issues/year

Canadian Journal of Statistics - Revue Canadienne de Statistique is a prestigious publication in the field of statistics, managed by Wiley. Since its inception in 1973, this journal has served as an essential resource for researchers, practitioners, and students, offering insights into a diverse range of statistical methodologies and applications. With its impact reflected in its 2023 categorization as Q2 in Statistics and Probability and Q3 in Statistics, Probability and Uncertainty, the journal stands out among its peers, exemplifying rigorous standards in empirical research. The journal's ISSN is 0319-5724 and its E-ISSN is 1708-945X, providing a robust platform for the dissemination of knowledge in the field. While it does not offer open access, the journal remains highly regarded and well-cited, contributing significantly to the advancement of statistical theory and practice. As it continues to publish cutting-edge research through to 2024, the Canadian Journal of Statistics is a must-read for anyone seeking to stay informed on the latest trends and developments in statistics.

STATISTICAL SCIENCE

Advancing the Frontiers of Statistical Methodology.
Publisher: INST MATHEMATICAL STATISTICS-IMSISSN: 0883-4237Frequency: 4 issues/year

STATISTICAL SCIENCE, published by the Institute of Mathematical Statistics (IMS), stands as a premier journal in the fields of Statistics and Probability, commencing its journey in 1986 and continuing through 2024. With an impressive track record reflected in its Q1 quartile rankings in Mathematics, Statistics and Probability, and Statistics, Probability and Uncertainty for 2023, it holds a distinguished position in the academic community. The journal is recognized for its rigorous peer-review process and for publishing high-quality research that significantly contributes to advancing statistical methodology and its applications across various domains. Researchers and professionals are encouraged to engage with its contents to stay abreast of the latest developments and methodologies in statistical science. Although it does not offer open access, the valuable insights provided within its pages are essential for any scholar dedicated to the pursue of statistical excellence. As you navigate the complexities of data analysis and interpretation, STATISTICAL SCIENCE is your go-to resource for groundbreaking research, innovative techniques, and comprehensive reviews.

TEST

Empowering researchers through rigorous statistical insights.
Publisher: SPRINGERISSN: 1133-0686Frequency: 3 issues/year

TEST, published by Springer, is a prestigious academic journal that serves as a vital platform for research in the fields of Statistics and Probability. With an ISSN of 1133-0686 and an E-ISSN of 1863-8260, TEST has been at the forefront of statistical methodology and applications since its inception in 1992. As of 2023, the journal holds a Q2 ranking in both the Statistics and Probability, and Statistics, Probability and Uncertainty categories, affirming its position among the leading scholarly publications in these domains. Although it currently does not offer open access, its rich repository of peer-reviewed articles and innovative research findings continues to attract attention from researchers, professionals, and students alike. Positioned within the competitive landscape of mathematical sciences, TEST aims to advance both theoretical developments and practical applications in statistical science through high-quality publications. Researchers can greatly benefit from the insights and methodologies presented within its pages, as elucidated by its Scopus rankings, placing it in the 56th percentile for Mathematics in Statistics and Probability and 53rd for Decision Sciences. For further inquiries, TEST is headquartered at One New York Plaza, Suite 4600, New York, NY 10004, United States, where it continually strives to contribute to the evolution of statistical research.

STATISTICS AND COMPUTING

Pioneering advancements in computational algorithms and methodologies.
Publisher: SPRINGERISSN: 0960-3174Frequency: 1 issue/year

Statistics and Computing is a premier journal published by Springer, dedicated to advancing the fields of statistics and computational theory. With a strong focus on interdisciplinary research, this journal covers a broad spectrum of topics including, but not limited to, statistical methodologies, computational algorithms, and the latest advancements in data analysis. As of 2023, it proudly holds a Q1 ranking in multiple categories including Computational Theory and Mathematics and Statistics and Probability, underscoring its significant influence and recognition within the academic community. The journal's impact is further demonstrated by its commendable positions in Scopus ranks, making it a valuable resource for researchers, professionals, and students alike. Published in the Netherlands, Statistics and Computing is known for its rigorous peer-review process and commitment to quality, ensuring that only the most impactful research is disseminated to the global audience. Submissions from a diverse range of backgrounds are encouraged, fostering an inclusive environment for innovation and collaboration in the statistics and computing realm.

Thailand Statistician

Your Gateway to High-Quality Statistical Research
Publisher: THAI STATISTICAL ASSOCISSN: 1685-9057Frequency: 2 issues/year

Thailand Statistician, published by the THAI STATISTICAL ASSOCIATION, is a pivotal journal in the realms of computational mathematics and statistics. With an ISSN of 1685-9057 and an E-ISSN of 2351-0676, this journal aims to disseminate high-quality research and innovative methodologies that advance the fields of statistics and probability. Covering a range of topics from theoretical statistics to applied computational techniques, it provides a platform for researchers, professionals, and students in Thailand and beyond to contribute their findings and insights. The journal has been gaining recognition, boasting a Scopus ranking of Q3 in Computational Mathematics and Q4 in Statistics and Probability as of 2023. With its commitment to open access, the Thailand Statistician stands as an essential resource for those striving to stay abreast of advancements in statistical methodologies and their applications, fostering the growth of statistical science in the region and globally.

Metron-International Journal of Statistics

Elevating the discourse in statistics and probability.
Publisher: SPRINGER-VERLAG ITALIA SRLISSN: 0026-1424Frequency: 3 issues/year

Metron-International Journal of Statistics is a prestigious peer-reviewed journal published by SPRINGER-VERLAG ITALIA SRL, dedicated to advancing the field of statistics and probability. With an ISSN of 0026-1424 and an E-ISSN of 2281-695X, this journal has been a vital platform for scholarly research since its inception in 1973, showcasing works that redefine methodologies and applications within the field. Positioning itself in Q3 of the 2023 statistics category quartiles, Metron aims to foster dialogue and innovation among researchers and practitioners. Although currently not an open-access publication, it provides invaluable insights that contribute significantly to the statistical community's body of knowledge. Serving a diverse global audience, the journal encourages submissions that address both theoretical frameworks and practical applications in statistics, promising to enhance the rigor and relevance of statistical practice. Based in Milan, Italy, Metron continues to uphold its commitment to excellence in statistical research through thorough peer review and a focus on impactful findings.

COMPUTATIONAL STATISTICS

Pioneering research in the realm of computational statistics.
Publisher: SPRINGER HEIDELBERGISSN: 0943-4062Frequency: 4 issues/year

COMPUTATIONAL STATISTICS, published by Springer Heidelberg, is a prominent international journal that bridges the fields of computational mathematics and statistical analysis. Since its inception in 1996, this journal has served as a critical platform for disseminating high-quality research and advancements in statistical methodologies and computational techniques. Operating under Germany's esteemed scholarly tradition, it holds a commendable Q2 ranking in key categories such as Computational Mathematics and Statistics and Probability, reflecting its significant impact and relevance in the academic community. Although it does not offer Open Access, the journal remains a vital resource for researchers, professionals, and students seeking to enhance their understanding of the intricate interplay between computation and statistical inference. Each issue features rigorously peer-reviewed articles that contribute to the development of innovative methodologies and applications, thereby solidifying its role in shaping the future of computational statistics.

Stats

Exploring the frontiers of probability and statistics.
Publisher: MDPIISSN: Frequency:

Stats, published by MDPI, serves as an invaluable open access platform dedicated to the fields of statistics and probability. Since its inception in 2018, the journal has been committed to disseminating high-quality research and promoting innovation in statistical methodologies through a rigorous peer-review process. Operating from Basel, Switzerland, Stats offers a global reach and aims to foster collaboration among researchers, professionals, and graduate students alike. With an impact factor indicating its emerging significance, the journal resides in the Q4 quartile of the statistics and probability category for 2023 according to Scopus rankings. This positions it within the evolving landscape of statistical research, enhancing its visibility and accessibility. Researchers are encouraged to contribute to this dynamic field and benefit from the journal's dedication to open access publishing, ensuring that research findings can reach a broad audience without barriers.