Downloads

Schlickeiser, R., & Kröger, M. Editorial of Applied Statistical Analysis and Computing (ASAC). Applied Statistical Analysis and Computing. 2024. doi: Retrieved from https://www.sciltp.com/journals/asac/article/view/645
Volume 1, Issue 1, 2025
Copyright (c) 2024 by the authors.
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Editorial

Editorial of Applied Statistical Analysis and Computing (ASAC)

Reinhard Schlickeiser 1,2,∗ and Martin Kröger 3,∗

1 Institut fur Theoretische Physik, Lehrstuhl IV: Weltraum- und Astrophysik, Ruhr-Universitat Bochum, D-44780 Bochum, Germany

2 Institut fur Theoretische Physik und Astrophysik, Christian-Albrechts-Universitat zu Kiel, Leibnizstr. 15, D-24118 Kiel, Germany

3 Magnetism and Interface Physics & Computational Polymer Physics, Department of Materials, ETH Zurich, Leopold- Ruzicka-Weg 4, CH-8093 Zurich, Switzerland

∗ Correspondence: rsch@tp4.rub.de (R.S.); mk@mat.etz.ch (M.K.)

Received: 10 October 2024 ; Accepted: 30 November 2024; Published: 6 December 2024

Launching a new journal always is a risky endeavour especially in well-established fields of research such as statistical analysis. The reason is very simple: if one has written an excellent paper one wants to have it published in an esteemed journal. Why should one send it to a new journal, where almost nobody might see it? One of our former colleagues referred to this as “first-class funeral”. It definitely needs year-long perseverance and attractive offers to the authors (e.g. fast but solid reviewing, quick publication time, open access option) to establish new journals. We trust that our publisher Scilight press lives up to these challenges.

On the other hand the scientific landscape has changed substantially compared to earlier decades. Practically every new submission is pre-published today on preprint servers after some very light screening so that it does not matter that much anymore where the manuscript finally will be published. Preprint servers and open-access journals play an important rule as many institutions cannot afford the often costly subscription fees of traditional journals. Moreover, the rapid advancement of artificial intelligence will reflect itself in the subject and content of future scientific submissions. Often it is difficult to judge on the authorships of submissions being due to individual scientists or to intelligent bots. Submissions by latter ones is not really in the interest of true science by human beings.

Statistical methods, analysis and computing plays an important role in many scientific disciplines not only in natural science disciplines. We aim to establish a new journal where contributions from different scientific fields find a new home which will lead to an open discussion and exchange of new ideas and developments that advance the field of statistical research. Our priorities lie at the interface of

  1. math-oriented applied statistical analysis and computing, including big data analysis, data mining and visualization, predictive modeling, and Monte Carlo methods,
  2. innovativealgorithms in statistical computing, machine learning for statistical modeling,
  3. theapplication of statistical methods to time-dependent or spatial data, including forecasting, clustering, and anomaly detection, analytical and computational approaches in biostatistics to address problems in biology, epidemiology, and healthcare,
  4. applications of statistical techniques to problems in financial data analysis, econometrics, and risk man- agement, as well as quantitative social science applying statistical models to problems in sociology, political sci- ence, and other social sciences.

We welcome the submission of high-quality manuscripts subjecting this interdisciplinary field. These include pioneering new statistical methods as well as their applications in different scientific fields.