This journal publishes research on statistical workflows, encompassing the development, evaluation, and application of models and data science methodologies. It explores the integration of statistical techniques with machine learning and artificial intelligence for tasks such as forecasting, prediction, and knowledge discovery across various scientific domains. The journal also addresses the challenges of reproducibility, uncertainty quantification, and the interpretation of results within complex data analysis pipelines.
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Publication & Citation Trend
Articles published
Times cited
2019
2020
2021
2022
2023
2024
2025
2026
Source: OpenAlex · Note: citations accumulate over time so older years appear higher
SJR Quartile by Discipline
Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.
Engineering (miscellaneous)Q1
Mathematics (miscellaneous)Q1
Physics and Astronomy (miscellaneous)Q1
Subject Classification
Web of Science Categories
Multidisciplinary Sciences
Scopus Categories
Mathematics (miscellaneous)Engineering (miscellaneous)Physics and Astronomy (miscellaneous)
Research Topics (OpenAlex)
Fluid Dynamics and Turbulent FlowsAstro and Planetary ScienceQuantum Mechanics and ApplicationsNonlinear Dynamics and Pattern FormationGeology and Paleoclimatology ResearchClimate variability and modelsHigh-pressure geophysics and materialsQuantum Information and CryptographyAtmospheric and Environmental Gas DynamicsSolar and Space Plasma Dynamics