Restructuring of Sections of Stats (ISSN 2571-905X)

Stats (ISSN 2571-905X) [1] is an international, open-access journal dedicated to statistical science. It provides an advanced forum for research on statistical methodology, theoretical developments, and their applications.

Established in 2018, Stats was accepted for inclusion in the Emerging Sources Citation Index (ESCI) within the Web of Science Core Collection in 2022 [2]. In response to the journal’s rapid growth, its scope was subsequently organized into 17 sections encompassing a broad range of statistical disciplines. To reflect continuing advances in statistical science and the evolving research landscape, the journal has recently undertaken a strategic restructuring of these sections. This initiative is intended to provide clearer and more intuitive navigation for authors and readers across diverse statistical fields.

Table 1. Original and new section structures of Stats.

Original Section Structure	New Section Structure
Applied Stochastic Models	Statistical Theory and Methods
Bayesian Methods
Multivariate Analysis
Regression Models
Statistical Methods
Bioinformatics	Biostatistics
Biostatistics
Survival Analysis
Applied Statistics and Machine Learning Methods	Data Science, Machine Learning and Artificial Intelligence
Computational Statistics
Data Science
Statistical Software
Econometric Modelling	Econometrics & Financial Statistics
Financial Statistics
Ecological Statistics	General Applied Statistics
Reliability Engineering
Time Series Analysis

presents both the original and the newly revised section structures of the journal.

Importantly, this restructuring does not alter the journal’s core scope or mission. Rather, it reflects our commitment to keeping pace with the rapid development of statistical science, particularly in statistical and machine learning and big data analytics. The revised structure also ensures that major areas of application—from biostatistics and econometrics to ecology and reliability—are explicitly represented and readily accessible.

We hope that this refined organizational structure will offer authors and readers a clearer pathway to relevant content while fostering interdisciplinary collaboration across the broad spectrum of statistical research.