Directional Statistics: Series C seeks submissions for special journal issue

The editors of the Journal of the Royal Statistical Society, Series C are seeking submissions for an upcoming special edition: 'Directional Statistics’ 

Deadline for submissions: 28 February 2026 

Call 

This special issue will gather innovative contributions and recent methodological advances in Directional Statistics, a vibrant subfield of statistics focused on data defined on circular, spherical or more general manifolds. Directional data arise naturally in many scientific disciplines such as geology, meteorology, biology, neuroscience, and environmental science, where measurements correspond to angles, axes or directions rather than conventional linear quantities. 

The analysis of directional data presents unique challenges due to their intrinsic geometric constraints and periodicity. Standard Euclidean statistical methods are often inappropriate, necessitating the development of specialised techniques and models tailored to the topology of directional spaces. The special issue aims to provide a platform for cutting-edge research in methodology related to a specific real data problem and in the original application of directional data analysis, fostering cross-disciplinary collaboration and highlighting emerging trends. 

Contributions to this special issue are invited in, but not limited to, the following topics: 

  • Parametric, semi-parametric and nonparametric models for circular and spherical data 

  • Regression models with directional responses and/or predictors 

  • Methods for inference on manifolds and related geometrical structures 

  • Clustering and classification of directional data 

  • Directional time series and spatio-temporal models on spheres 

  • Bayesian approaches to directional statistics 

  • High-dimensional directional data analysis 

  • Visualization techniques for directional data 

  • Applications in environmental sciences, biology, neuroscience, astronomy, and engineering 

  • Computational algorithms and software for directional statistics 

  • Diagnostics, model selection and goodness-of-fit methods for directional models 

Authors uncertain about the suitability of their work for this special issue are encouraged to submit a preliminary abstract or draft to the guest editors for initial feedback. All submissions will undergo the journal’s standard peer review process, with handling by the Special Issue Editors.  

Manuscripts should be submitted by 28 February 2026 through the online submission system at https://mc.manuscriptcentral.com/jrssc 

When submitting, please select the option indicating that the paper is for a special issue and specify “Directional Statistics” in the Special Issue Information field. 

Submitted manuscripts must adhere to the journal’s instructions for authors, available on the journal’s website. We welcome both theoretical and applied papers, but all contributions must demonstrate statistical rigor and relevance to directional data problems. We seek papers that are tackling genuine problems in directional statistics, where applications are central to the paper and provide the motivation for the work presented. Papers should directly engage with the application and should clearly indicate what additional insights into the applied problem have been gained by applying the suggested methodology. Papers solely focusing on algorithmic development without sufficient statistical context or motivation are discouraged. 

The quality of language is important; authors are advised to consider professional editing support if necessary. 

We anticipate that this special issue will benefit researchers and practitioners across diverse disciplines. Although not mandatory, submissions from participants to the International Workshop on Advances in Directional Statistics 2025 (ADISTA25) in Luxembourg are particularly welcome. 

Christophe Ley (christophe.ley@uni.lu) 

Toshihiro Abe (abetosh@hosei.ac.jp) 

Rosa Crujeiras (rosa.crujeiras@usc.es) 

Load more