The Journal of Statistical Planning and Inference bridges classical statistics and probability with emerging interdisciplinary aspects. It maintains traditional strengths in statistical inference, design, classical probability, and large sample methods, while also broadening its scope to include areas such as clustering, post model selection inference, deep learning, and random networks.
Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.
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.
Applied MathematicsQ2
Statistics and ProbabilityQ2
Statistics, Probability and UncertaintyQ2
Subject Classification
Web of Science Categories
Statistics & Probability
Scopus Categories
Applied MathematicsStatistics, Probability and UncertaintyStatistics and Probability
Research Topics (OpenAlex)
Statistical Methods and InferenceOptimal Experimental Design MethodsAdvanced Statistical Methods and ModelsStatistical Methods and Bayesian InferenceStatistical Distribution Estimation and Applications