Aims and Scope
Modern Journal of Statistics (MJS) is an open-access, international, peer-reviewed journal dedicated to publishing high-quality research that advances statistics' theory, methods, and applications. The journal serves as a platform for statisticians, data scientists, and applied researchers to present novel solutions to real-world problems and contribute to the ongoing development of modern statistical techniques.
We welcome original research articles, review papers, and practical application studies that offer:
- Novel statistical methods with solid theoretical foundations.
- Creative and applicable solutions to complex data challenges.
- Meaningful applications of existing methods in statistics to emerging and
- interdisciplinary areas.
The journal covers a wide range of topics, including but not limited to:
- Applied and mathematical statistics.
- Bayesian inference and estimation.
- Biostatistics and biomedical applications.
- Data science implementations.
- Econometrics and financial statistics.
- Functional data analysis.
- Linear and non-linear modeling approaches.
- Multivariate statistical analysis.
- Nonparametric and semi-parametric methods.
- Probability theory and applications.
- Statistical computing and simulation techniques.
- Survival and reliability analysis.
- Time series analysis and forecasting.
- Stochastic processes.
- Queuing theory.
- Fuzzy probability.
MJS also welcomes proposals for special issues that align with the journal's aims and contribute to emerging areas of statistical research.
By submitting to this journal, the authors affirm that the work is original, has not been previously published, and is not currently under review by any other publisher. Duplicate submissions are prohibited.
