Journal of Computational and Graphical Statistics - Taylor & Francis | 2024 Impact Factor:1.8 | Cite Score:3.4 | Q1

Impact Factor and Journal Rank of Computational and Graphical Statistics

• About: The Journal of Computational and Graphical Statistics (JCGS) is a premier publication in the field of statistical science, jointly published by the American Statistical Association, the Institute of Mathematical Statistics, and the Interface Foundation of North America. The journal aims to advance the understanding and application of computational and graphical methods in statistics, promoting research that bridges the gap between statistical theory and practice.
• Objective: The journal aims to publish research that advances the use of computational and graphical methods in statistics, enhancing the ability to analyze complex data and interpret results visually.
• Focus Areas:
  Computational statistics and algorithms
  Statistical graphics and data visualization
  High-dimensional data analysis
  Bayesian computation and modeling
  Machine learning and statistical learning methods
  Statistical software development and applications
  Simulation and Monte Carlo methods
  Nonparametric and semiparametric methods
  Applications of computational and graphical methods in various scientific fields
• Impact and Significance:
  The journal serves as a critical platform for statisticians, data scientists, and researchers to share innovative methodologies and applications in computational and graphical statistics.
  It contributes significantly to the development of new techniques and tools that improve data analysis, interpretation, and presentation.
  The rigorous peer-review process ensures the publication of high-quality research that advances the state-of-the-art in computational and graphical statistics.

• Journal Home:  Journal Homepage

• Editor-in-Chief:  Galin Jones

• Scope: The journal covers a broad spectrum of topics related to computational and graphical methods in statistics, including but not limited to:
• Computational Statistics: Development and evaluation of algorithms for statistical computing, including numerical methods, optimization techniques, and simulation methods.
• Graphical Methods: Design and evaluation of graphical techniques for data visualization, including exploratory data analysis, dynamic graphics, and multivariate visualization methods.
• Statistical Software: Creation, testing, and dissemination of software tools and packages that implement new and existing statistical methods.
• Bayesian Methods: Computational techniques for Bayesian inference, including Markov Chain Monte Carlo (MCMC) methods, variational approaches, and Bayesian model averaging.
• High-Dimensional Data: Methods for analyzing and visualizing high-dimensional datasets, including techniques for dimension reduction, sparse modeling, and feature selection.
• Nonparametric Methods: Development and application of nonparametric techniques in computational statistics, including kernel methods, splines, and rank-based methods.
• Machine Learning: Statistical aspects of machine learning, including supervised and unsupervised learning, ensemble methods, and deep learning.
• Data Science Applications: Case studies and applications of computational and graphical methods in various domains, such as bioinformatics, finance, social sciences, and environmental science.
• Statistical Theory: Theoretical contributions that provide insights into the behavior and properties of computational and graphical methods.
• Methodological Innovations: Novel methodological approaches that improve the efficiency, accuracy, and interpretability of statistical analyses.
• Latest Research Topics for PhD in Computer Science

• Print ISSN:  10618600

  Electronic ISSN:  15372715

• Abstracting and Indexing:  Science Citation Index Expanded, Scopus

• Imapct Factor 2024:  1.8

• Subject Area and Category:  Decision Sciences Statistics, Probability and Uncertainty,Mathematics,Discrete Mathematics and Combinatorics,Statistics and Probability

• Publication Frequency:  

• H Index:  108

• Best Quartile:

  Q1:  Discrete Mathematics and Combinatorics

  Q2:  

  Q3:  

  Q4:  

• Cite Score:  3.4

• SNIP:  1.398

• Journal Rank(SJR):  1.241

• Latest Articles:   Latest Articles in Journal of Computational and Graphical Statistics

• Guidelines for Authors: Journal of Computational and Graphical Statistics Author Guidelines

• Paper Submissions: Paper Submissions in Journal of Computational and Graphical Statistics

• Publisher:  Taylor and Francis Ltd.

  Country:  United Kingdom

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