METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY

metrics 2024

Exploring the synergy between probability and computational techniques.

Introduction

METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY is a distinguished journal published by SPRINGER, dedicated to advancing research in applied probability and its relationship with various computational methodologies. With an ISSN of 1387-5841 and an E-ISSN of 1573-7713, this journal provides a platform for innovative studies that bridge theory and practical application in the field of mathematics and statistics. Ranking in the Q2 category for Mathematics (miscellaneous) and Q3 for Statistics and Probability as of 2023, it reflects a robust academic discourse, featuring contributions that span a range of methodologies utilized in probability-related studies. The journal's sustained engagement in the academic landscape from 2004 to 2024 puts it at the forefront of ongoing developments in statistics and probability. Researchers, professionals, and students alike will find the insights found within to be invaluable for both theoretical understanding and practical implementation.

Metrics 2024

SCIMAGO Journal Rank0.43
Journal Impact Factor1.00
Journal Impact Factor (5 years)0.90
H-Index35
Journal IF Without Self1.00
Eigen Factor0.00
Normal Eigen Factor0.31
Influence0.41
Immediacy Index0.30
Cited Half Life6.80
Citing Half Life13.60
JCI0.51
Total Documents1131
WOS Total Citations867
SCIMAGO Total Citations2536
SCIMAGO SELF Citations171
Scopus Journal Rank0.43
Cites / Document (2 Years)1.14
Cites / Document (3 Years)1.06
Cites / Document (4 Years)1.04

Metrics History

Rank 2024

Scopus

General Mathematics in Mathematics
Rank #138/399
Percentile 65.41
Quartile Q2
Statistics and Probability in Mathematics
Rank #159/278
Percentile 42.81
Quartile Q3

IF (Web Of Science)

STATISTICS & PROBABILITY
Rank 93/168
Percentile 44.90
Quartile Q3

JCI (Web Of Science)

STATISTICS & PROBABILITY
Rank 88/168
Percentile 47.62
Quartile Q3

Quartile History

Similar Journals

BERNOULLI

Elevating Statistical Theory and Application
Publisher: INT STATISTICAL INSTISSN: 1350-7265Frequency: 4 issues/year

BERNOULLI is a prestigious peer-reviewed journal dedicated to the field of Statistics and Probability, published by the renowned International Statistical Institute. Since its inception in 1995, this journal has established itself as a vital resource for researchers and professionals, achieving a remarkable impact factor and consistently ranking in the top quartile (Q1) of its category as of 2023. With a strong presence in the Scopus database, where it ranks #64 among 278 journals in Mathematics, it places in the 76th percentile, underscoring its significance in the academic landscape. Although not an open-access journal, its contributions are pivotal for advancing statistical theory and its applications across various disciplines. As Berounlli continues to evolve until 2024, it remains committed to disseminating high-quality research that fosters innovation and supports the global analytics community. The journal’s scope encompasses a wide range of topics in statistics, including but not limited to theoretical statistics, applied statistics, and data analysis, making it an essential read for anyone engaged in statistical research.

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.

Sankhya-Series A-Mathematical Statistics and Probability

Bridging Theory and Application in Mathematical Statistics
Publisher: SPRINGERISSN: 0976-836XFrequency: 2 issues/year

Sankhya-Series A-Mathematical Statistics and Probability is a prestigious academic journal published by SPRINGER, situated in the United States. With a focus on the rapidly evolving fields of mathematical statistics and probability, this journal serves as a critical platform for researchers, professionals, and students seeking to disseminate their findings and engage with latest advancements. Although it is not an open access publication, its rigorous peer-review process ensures high-quality content that contributes to the scholarly community. As of 2023, the journal is classified within the Q3 quartile in both Statistics and Probability, and Statistics, Probability and Uncertainty categories, reflecting its relevance and growing influence in the field. Sankhya-Series A showcases a convergence of interdisciplinary approaches, facilitating dialogue among statisticians and mathematicians, making it an essential resource for those committed to the exploration of theoretical and applied statistics. The journal accepts contributions advancing innovative research and methodologies, promoting a deeper understanding of probabilistic models and statistical techniques.

Sankhya-Series B-Applied and Interdisciplinary Statistics

Bridging Disciplines with Cutting-Edge Statistical Methodologies
Publisher: SPRINGERISSN: 0976-8386Frequency: 2 issues/year

Sankhya-Series B: Applied and Interdisciplinary Statistics, published by Springer in India, serves as a vital platform for advancing the field of applied statistics and interdisciplinary research. With an ISSN of 0976-8386 and an E-ISSN of 0976-8394, this journal has made significant contributions since its inception in 2010, continuing to publish impactful research until 2024. The journal is ranked in the third quartile across several categories, including Applied Mathematics and Statistics, reflecting its importance within the academic community. Although not an open-access journal, Sankhya-Series B provides robust access options for its readership, facilitating the dissemination and discussion of critical statistical methodologies and applications. Researchers, professionals, and students are encouraged to engage with the journal's comprehensive scope, which includes a focus on statistical theory, methodologies, and their practical applications across various disciplines. By providing a rigorous forum for scholarly exchange, this journal plays an essential role in shaping the future of applied statistics and fostering interdisciplinary collaboration.

Journal of the Indian Society for Probability and Statistics

Innovating Statistical Methodologies for a Dynamic World
Publisher: SPRINGERNATUREISSN: Frequency: 2 issues/year

Journal of the Indian Society for Probability and Statistics, published by SpringerNature in Germany, is a prominent platform dedicated to advancing the field of statistics and probability. With its E-ISSN of 2364-9569, the journal features rigorous research articles, reviews, and theoretical advancements aimed at promoting the application of statistical methodologies in diverse areas. As part of the academic community since 2016, it has maintained a commendable Q3 ranking in the Statistics and Probability category for 2023, indicating its growing influence and relevance. As the journal aims to foster collaborations among statisticians and probabilists, it serves as an invaluable resource for researchers, professionals, and students looking to deepen their understanding and share innovative ideas. While the journal operates under a subscription model, its commitment to open access publication contributes to the broader dissemination of knowledge in this vital field, further enhancing its importance and utility within the scientific landscape.

Stat

Fostering collaboration in the evolving landscape of statistics.
Publisher: WILEYISSN: 2049-1573Frequency: 1 issue/year

Stat is a respected academic journal published by WILEY, focusing on the vital fields of Statistics and Probability. Established in 2012 and converging through to 2024, this journal offers critical insights and advancements in statistical methodologies and applications. While it operates under traditional access options, researchers and practitioners can benefit from its rigorous peer-reviewed content, which serves to stimulate innovation and collaboration in statistics. In the 2023 categorizations, Stat has been recognized in the Q3 quartile in both Statistics and Probability and Statistics, Probability and Uncertainty, reflecting its growing influence and relevance in the field. Positioned within a competitive landscape, with Scopus ranks highlighting its challenges and opportunities, Stat is an essential resource for academics, professionals, and students seeking to deepen their understanding and application of statistical techniques. As the journal continues to evolve, it remains committed to fostering a community of inquiry and practice in statistics.

JOURNAL OF APPLIED PROBABILITY

Innovating Solutions with Probability Insights
Publisher: CAMBRIDGE UNIV PRESSISSN: 0021-9002Frequency: 4 issues/year

JOURNAL OF APPLIED PROBABILITY is a prestigious peer-reviewed journal published by Cambridge University Press, focusing on the intricate interactions between probability theory and its applications in diverse scientific fields. With a rich history dating back to 1975, this journal caters to an audience of researchers, professionals, and students interested in advancing their knowledge in areas such as mathematics, statistics, and decision sciences. The journal thrives in the competitive landscape of academia, boasting a respectable impact factor and earning Q2 rankings in both Mathematics and Statistics categories as of 2023. It provides a platform for innovative research and methodologies that bridge theoretical concepts with real-world applications, thereby enriching the discipline of applied probability. Although it is not an open-access journal, the JOURNAL OF APPLIED PROBABILITY ensures comprehensive access options through institutional subscriptions, making it a vital resource for anyone engaged in sophisticated probabilistic analysis and its practical implementations.

COMPUTATIONAL STATISTICS & DATA ANALYSIS

Exploring New Dimensions in Data Analysis
Publisher: ELSEVIERISSN: 0167-9473Frequency: 12 issues/year

COMPUTATIONAL STATISTICS & DATA ANALYSIS, published by Elsevier, is a leading academic journal that has made significant contributions to the fields of Applied Mathematics, Computational Mathematics, Computational Theory and Mathematics, and Statistics and Probability. With an impressive ranking of Q1 in multiple categories, this journal stands at the forefront of scholarly research and innovation. Leveraging its digital accessibility through E-ISSN 1872-7352, the journal facilitates the dissemination of high-quality research findings and methodologies essential for advancing statistical techniques and data analysis applications. Operating from its base in Amsterdam, Netherlands, the journal features rigorous peer-reviewed articles that cater to a diverse readership including researchers, professionals, and students. As a vital resource for cutting-edge developments from 1983 to its ongoing publication in 2025, COMPUTATIONAL STATISTICS & DATA ANALYSIS continues to foster academic discourse and propel the field forward, ensuring that emerging trends and established theories are effectively communicated to the scientific community.

Statistical Inference for Stochastic Processes

Pioneering the future of stochastic process analysis.
Publisher: SPRINGERISSN: 1387-0874Frequency: 3 issues/year

Statistical Inference for Stochastic Processes is a premier academic journal published by SPRINGER, dedicated to advancing the field of statistical methods in stochastic processes. With an ISSN of 1387-0874 and an E-ISSN of 1572-9311, this journal provides a platform for rigorous research and innovative methodologies from 2005 through to 2024. It is positioned in the Q3 category for Statistics and Probability, ranking #194 out of 278 within the Scopus Mathematics domain, reflecting its significance among academic peers despite its relatively junior status in citation metrics. As a resource for researchers, professionals, and students alike, this journal aims to publish high-quality, peer-reviewed articles that contribute to the understanding and application of stochastic processes, making it an essential part of the statistical sciences landscape. While not offering open access, subscribers and institutions will find a wealth of knowledge and insights that are pivotal for both theoretical and practical advancements in statistics.

Monte Carlo Methods and Applications

Innovating Monte Carlo Applications for Tomorrow's Challenges
Publisher: WALTER DE GRUYTER GMBHISSN: 1569-3961Frequency: 4 issues/year

Monte Carlo Methods and Applications is an esteemed academic journal published by WALTER DE GRUYTER GMBH based in Germany, specializing in the fields of applied mathematics and statistics. With its ISSN 1569-3961 and E-ISSN 0929-9629, the journal has made significant contributions to the methodology and application of Monte Carlo techniques since its inception in 1995. As a vital resource for researchers, professionals, and students, it provides a platform for disseminating cutting-edge research, innovative methodologies, and diverse applications related to Monte Carlo simulations. Despite its current standing in the Q4 category for both applied mathematics and statistics, the journal is poised for growth and engagement within the academic community, helping to bridge the gap between theoretical advances and practical implementations. The journal's emphasis on rigorous peer-reviewed content ensures the highest quality of publications, making it a reliable source for pivotal insights in the realm of probabilistic modeling and computation.