Electronic Journal of Statistics, published by INST MATHEMATICAL STATISTICS-IMS, is a premier open-access platform dedicated to the field of statistics and probability, with a remarkable track record since its inception in 2007. With an ISSN of 1935-7524, this journal has quickly established itself as a leading resource within the top Q1 category in both Statistics and Probability, as well as Statistics, Probability and Uncertainty, highlighting its significance and impact in the academic community. The journal’s commitment to disseminating high-quality research allows researchers, professionals, and students to access valuable findings and methodologies that contribute to the advancement of statistical sciences. With its convergence set to continue until 2024, the Electronic Journal of Statistics remains a vital source for scholars looking to enrich their knowledge and engage with cutting-edge statistical theories and applications.

The Annals of Applied Statistics, published by the Institute of Mathematical Statistics (IMS), is a leading academic journal that serves as a crucial repository for groundbreaking research in the fields of statistics and probability applications. Since its inception in 2008 and continuing through 2024, this journal has established itself as an influential platform with a notable reputation, boasting a prestigious Q1 classification in 2023 across critical categories such as Modeling and Simulation and Statistics, Probability, and Uncertainty. With its rigorous peer-review process and significant Scopus rankings—including a position of #78 in Statistics and Probability—Annals of Applied Statistics aims to foster innovative statistical methods and their applications in a variety of disciplines. Researchers, professionals, and students interested in the latest advancements in analytical methods will find this journal essential for navigating the evolving landscape of applied statistics. The journal does not offer open access options, ensuring that published content reflects the highest academic standards.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, published by Taylor & Francis Ltd, is a premier journal dedicated to advancing the fields of statistical computation, modeling, and simulation. With a notable impact factor and a ranking in the Q2 quartile across important categories such as Applied Mathematics and Statistics, this journal serves as a vital resource for researchers, practitioners, and students alike. Established in 1972, it has consistently provided cutting-edge research insights, fostering a deeper understanding of statistical methodologies and their practical applications. Although it operates under a subscription model, the journal's commitment to disseminating high-quality research is reflected in its rigorous peer-review process and a broad international readership. With its scope spanning the intersections of statistics, probability, and computational techniques, the journal is essential for anyone looking to stay at the forefront of statistical innovation and practice.

JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES, published by TARU PUBLICATIONS, is a vital platform for researchers and practitioners in the field of information science and optimization techniques. With a focus on the application of mathematical and computational methods to solve complex problems in various domains, this journal aims to advance knowledge and encourage innovative thinking. The journal's ISSN is 0252-2667 and the E-ISSN is 2169-0103. Although currently not Open Access, it strives to provide high-quality research that significantly contributes to the industry. With a commitment to rigor and excellence, the JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES is essential for anyone dedicated to enhancing their understanding and application of optimization methodologies in an ever-evolving technological landscape.

ACM Transactions on Knowledge Discovery from Data (TKDD), published by the Association for Computing Machinery, is a prestigious journal at the forefront of the interdisciplinary realm of data mining and knowledge discovery. With an impressive Q1 ranking in Computer Science and a Scopus rank of #43 out of 232, this journal stands out as a top-tier resource for innovative research that addresses complex challenges in data science. Covering impactful studies from 2007 to 2024, TKDD presents cutting-edge algorithms, methodologies, and applications that shape the future of knowledge extraction from vast datasets. While not an open-access journal, it provides a platform for researchers, professionals, and students to disseminate their findings and engage with the latest advancements in this rapidly evolving field. By fostering collaboration and knowledge sharing, TKDD plays a vital role in advancing the understanding and application of data analysis techniques, making it an essential read for anyone involved in the pursuit of knowledge from data.

JOURNAL OF CLASSIFICATION, published by Springer, stands as a premier academic platform dedicated to the advancement of classification methodologies across various disciplines. With an ISSN of 0176-4268 and E-ISSN of 1432-1343, this esteemed journal has been pivotal since its inception in 1984, showcasing influential research that continues to shape the fields of Library and Information Sciences, Mathematics, Psychology, and Statistics. As reflected in its 2023 quartile rankings—Q2 in Library and Information Sciences, Mathematics (miscellaneous), and Psychology (miscellaneous), as well as Q3 in Statistics, Probability and Uncertainty—the journal is recognized for its high standard of scholarly contributions. Notably, its Scopus rankings highlight its significant impact, particularly in Mathematics (ranked #12/90) and Psychology (ranked #21/97), placing it among the elite publications in these fields. Although not an open access journal, it provides invaluable insights for researchers, professionals, and students seeking to deepen their understanding of classification theory and its practical applications. With convergence expected through 2024, the journal is well-positioned to further contribute to interdisciplinary discussions and innovations, solidifying its importance within the academic community.

Communications for Statistical Applications and Methods is a vital academic journal dedicated to advancing the field of statistics, with a particular focus on practical applications and methodologies. Published by the Korean Statistical Society, this journal has become a significant resource for researchers, practitioners, and students engaged in statistical sciences and its diverse applications in various fields including finance and modeling. Operating without an Open Access format, the journal is accessible through institutional subscriptions, allowing a broad audience to benefit from its insights. The journal covers works from its inception in 2017 to 2024, and although it currently ranks in the Q4 and Q3 quartiles across various mathematical and statistical categories, its commitment to quality research makes it a noteworthy platform for emerging trends and innovations. The journal not only serves to disseminate knowledge but also fosters collaboration among statisticians, ensuring that crucial advancements in statistical applications are communicated effectively.

STATISTICA NEERLANDICA is a prestigious peer-reviewed journal published by Wiley, focusing on the fields of statistics and probability. Established in 1946 and addressing key issues in statistical theory and its applications, the journal has significantly contributed to the development of modern statistical practices. With an impressive Q2 categorization in both Statistics and Probability, as well as Statistics, Probability, and Uncertainty, STATISTICA NEERLANDICA stands out within its field, ranking in the 62nd percentile among its peers in mathematics, specifically in statistics and probability. Researchers, professionals, and students can benefit from its rigorous scholarship and innovative methodologies, aiding in the advancement of statistical science. Although the journal does not operate under an open access model, it maintains a commitment to disseminating high-quality research, making it a vital resource for those engaged in statistical inquiry.

STATISTICS is a distinguished journal published by Taylor & Francis Ltd, dedicated to advancing the field of statistical science since its inception in 1985. With a strong focus on both the theoretical and practical aspects of Statistics and Probability, this journal serves as a vital platform for researchers, professionals, and students seeking to disseminate their findings and contribute to critical discussions in the discipline. Although categorized in the Q3 quartile for both Statistics and Probability and Statistics, Probability and Uncertainty, the journal's commitment to quality research is evidenced by its inclusion in relevant Scopus rankings. It holds respectable positions, ranked #132/168 in Decision Sciences and #219/278 in Mathematics. By providing a venue for high-quality research articles and reviews, STATISTICS aims to foster innovation, reinforce methodological advancements, and address contemporary challenges in statistical applications. The journal does not currently offer open access, but it is widely distributed, ensuring that significant research reaches the communities that need it most. Researchers are encouraged to submit their work to this essential resource that continues to shape the landscape of statistical inquiry.

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.