Statistics
Published by Taylor & Francis
ISSN : 0233-1888 eISSN : 1029-4910
Abbreviation : Statistics
Aims & Scope
Statistics publishes papers developing and analysing new methods for any active field of statistics, motivated by real-life problems.
Papers submitted for consideration should provide interesting and novel contributions to statistical theory and its applications with rigorous mathematical results and proofs.
Moreover, numerical simulations and application to real data sets can improve the quality of papers, and should be included where appropriate.
Statistics does not publish papers which represent mere application of existing procedures to case studies, and papers are required to contain methodological or theoretical innovation.
Topics of interest include, for example, nonparametric statistics, time series, analysis of topological or functional data.
Furthermore the journal also welcomes submissions in the field of theoretical econometrics and its links to mathematical statistics.
View Aims & ScopeMetrics & Ranking
Impact Factor
| Year | Value |
|---|---|
| 2025 | 1 |
| 2024 | 1.20 |
SJR (SCImago Journal Rank)
| Year | Value |
|---|---|
| 2024 | 0.439 |
Quartile
| Year | Value |
|---|---|
| 2024 | Q3 |
h-index
| Year | Value |
|---|---|
| 2024 | 41 |
Journal Rank
| Year | Value |
|---|---|
| 2024 | 12889 |
Journal Citation Indicator
| Year | Value |
|---|---|
| 2024 | 202 |
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 Decision Sciences and Mathematics, designed to support cutting-edge academic discovery.
Most Cited Articles
The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.
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CAPABILITY MEASURES FOR m -DEPENDENT STATIONARY PROCESSES
Citation: 442
Authors: SY-MIEN, YU-SHENG, W. L.
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Approximate discrete-time schemes for statistics of diffusion processes
Citation: 177
Authors: Danielle
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Cross-validated estimations in the single-functional index model
Citation: 114
Authors: Ahmed, Frédéric, Rabah, Philippe