Journal of the Indian Society for Probability and Statistics
Published by Springer Nature
eISSN : 2364-9569
Abbreviation : J. Indian Soc. Probab. Stat.
Aims & Scope
The Journal of the Indian Society for Probability and Statistics is dedicated to advancing research in probability, statistics, and their applications across various fields of science and technology.
The journal provides a platform for original theoretical and applied contributions that deepen understanding of probabilistic models, statistical methodologies, and data-driven insights relevant to both regional and global contexts.
The Journal welcomes high-quality research articles, reviews, and methodological developments in probability theory, statistical inference, stochastic processes, Bayesian methods, multivariate analysis, data science, and computational statistics.
It encourages work that addresses contemporary challenges in diverse domains, including but not limited to finance, healthcare, environmental science, machine learning, and artificial intelligence.
Additionally, it supports contributions that bridge traditional statistical approaches with modern data science techniques, fostering interdisciplinary innovation.
Special emphases are provided on recent topics like statistical learning, deep learning, high-dimensional problems, semi-parametric models, biostatistics, random networks, bioinformatics etc.
View Aims & ScopeMetrics & Ranking
Journal Rank
| Year | Value |
|---|---|
| 2024 | 17854 |
Journal Citation Indicator
| Year | Value |
|---|---|
| 2024 | 70 |
Impact Factor
| Year | Value |
|---|---|
| 2024 | 0.80 |
SJR (SCImago Journal Rank)
| Year | Value |
|---|---|
| 2024 | 0.268 |
Quartile
| Year | Value |
|---|---|
| 2024 | Q4 |
h-index
| Year | Value |
|---|---|
| 2024 | 11 |
Impact Factor Trend
Abstracting & Indexing
Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.
Subjects & Keywords
Journal’s research areas, covering key disciplines and specialized sub-topics in Mathematics, designed to support cutting-edge academic discovery.