This journal publishes research on statistical methods for data analysis, including techniques for supervised learning, concept drift detection, and out-of-distribution detection. It also covers methods for parameter estimation in multi-fidelity settings, functional principal component analysis for relative data, and robust principal component analysis for multivariate data with outliers and missing values. Applications include modeling extreme values, analyzing computer model outputs, predicting remaining useful life of industrial systems, and forecasting electricity network faults.
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 MathematicsQ1
Modeling and SimulationQ1
Statistics and ProbabilityQ1
Subject Classification
Web of Science Categories
Statistics & Probability
Scopus Categories
Applied MathematicsStatistics and ProbabilityModeling and Simulation
Research Topics (OpenAlex)
Advanced Statistical Methods and ModelsOptimal Experimental Design MethodsAdvanced Statistical Process MonitoringStatistical Distribution Estimation and ApplicationsProbabilistic and Robust Engineering DesignStatistical Methods and Bayesian InferenceStatistics Education and MethodologiesStatistical Methods and InferenceAdvanced Multi-Objective Optimization AlgorithmsFault Detection and Control Systems