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Astrostatistics aims to gather new developments in statistical research that can be relevant to astronomical data, pedagogical articles or notebooks to teach astronomers some classical or new techniques, and astronomical results which rely on complex statistical analyses.
Astrophysics is experiencing a change of paradigm, from an object-driven to a data-driven science. Big surveys are already feeding huge data bases and this trend will only accelerate in the coming years. Managing this amount of observations is a challenge for astroinformatics, and analysing the data is a challenge for astrostatistics. In this section, we would like to focus on the latter, that is the knowledge extraction, the data mining, the statistical inference with the physics in mind. The practice of the astronomers confronted with the data is clearly changing, but the expertise and even the awareness in statistical tools is generally lacking, as well as the confidence in the meaningfulness of their outcomes.
The goal of Astrostatistics is to gather new developments in statistical research that can be relevant to astronomical data, pedagogical papers or notebooks to teach astronomers some classical or new techniques, and astronomical results which rely on complex statistical analyses. We thus accept submissions from statisticians and astronomers who are observers, theoreticians or experts in numerical simulations, of original research or papers presenting methods and/or codes.
Topics of interest within all areas of astronomy include, but are not limited to:
Supervised and unsupervised classification
Machine and Deep Learning
Obviously, astrostatistics is interdisciplinary, and the Open Access environment of Frontiers allows a wider visibility of this new discipline within the astronomical and statistical communities, as well as in other fields. Astronomical data are certainly specific and challenging, fostering interest in the statisticians, but it is always surprising to see how other disciplines sometimes have developed solutions for problems more similar that one could think of. We hope that this Astrostatistics section could act as a portal to this rapidly developing domain of research.
Indexed in: Google Scholar, DOAJ, CrossRef, SAO/NASA ADS, Scopus coming soon, Emerging Sources Citation Index, Inspire, CLOCKSS
PMCID: coming soon for all published articles
Astrostatistics welcomes submissions of the following article types: Brief Research Report, Data Report, Editorial, General Commentary, Hypothesis and Theory, Mini Review, Opinion, Original Research, Perspective, Review and Specialty Grand Challenge.
All manuscripts must be submitted directly to the section Astrostatistics, where they are peer-reviewed by the Associate and Review Editors of the specialty section.
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