Journal of the Royal Statistical Society. Series C: Applied Statistics

Aims & Scope

Series C (Applied Statistics) promotes papers that are focused on statistical methods for real life problems.

Applications should be central to papers, rather than illustrative, to motivate the work and to justify any methodological developments.

All papers should feature an adequate description of a substantial application and a justification for any new theory.

Case-studies may be particularly appropriate and should include some contextual details, though there should also be a novel statistical contribution, for instance by adapting or developing methodology, or by demonstrating the proper application of new or existing statistical methods to solve challenging applied problems.

Papers describing interdisciplinary work are especially welcome, as are those that give interesting novel applications of existing methodology or provide new insights into the practical application of methods, and papers explaining innovative analysis of generic applied problems but not necessarily focused on a particular application also have a place in Series C.

Short communications may also be appropriate.

Methodological papers that are not motivated by a genuine application are not acceptable; nor are papers that include only brief numerical illustrations or that mainly describe simulation studies of properties of statistical techniques.

However, papers describing developments in statistical computing are encouraged, provided that they are driven by practical examples.

Extended algebraic treatment should be avoided.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.3
2024	1.00

SJR (SCImago Journal Rank)

Year	Value
2024	0.646

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	83

Journal Rank

Year	Value
2024	8930

Journal Citation Indicator

Year	Value
2024	338

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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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.

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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.

• Algorithm AS 136: A K-Means Clustering Algorithm

  Citation: 7365

  Authors: J. A., M. A.

• A Non-Parametric Approach to the Change-Point Problem

  Citation: 2438

  Authors: A. N.

• Generalized Additive Models for Location, Scale and Shape

  Citation: 1889

  Authors: R. A., D. M.

• An Exploratory Technique for Investigating Large Quantities of Categorical Data

  Citation: 1689

  Authors: G. V.

• Regression Using Fractional Polynomials of Continuous Covariates: Parsimonious Parametric Modelling

  Citation: 1155

  Authors: Patrick, Douglas G.

• Informative Drop-Out in Longitudinal Data Analysis

  Citation: 1125

  Authors: P., M. G.

• Ridge Estimators in Logistic Regression

  Citation: 1020

  Authors: S. Le, J. C. Van

• Adaptive Rejection Sampling for Gibbs Sampling

  Citation: 953

  Authors: W. R., P.

• An Extension of Shapiro and Wilk's W Test for Normality to Large Samples

  Citation: 873

  Authors: J. P.

• Minimum Spanning Trees and Single Linkage Cluster Analysis

  Citation: 765

  Authors: J. C., G. J. S.

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