Introduction to papers on astrostatistics
Thomas J. Loredo, John Rice, Michael L. Stein

TL;DR
This paper introduces a special section on astrostatistics, highlighting the diverse statistical challenges in astronomy due to its observational nature, small or large data sets, and complex data-phenomenon relationships.
Contribution
It provides an overview of the statistical problems in astronomy and discusses recent developments and approaches in astrostatistics.
Findings
Diverse statistical challenges in astronomy due to data size and complexity
Necessity of balancing model sophistication and computational feasibility
Importance of uncertainty quantification in sparse data
Abstract
We are pleased to present a Special Section on Statistics and Astronomy in this issue of the The Annals of Applied Statistics. Astronomy is an observational rather than experimental science; as a result, astronomical data sets both small and large present particularly challenging problems to analysts who must make the best of whatever the sky offers their instruments. The resulting statistical problems have enormous diversity. In one problem, one may have to carefully quantify uncertainty in a hard-won, sparse data set; in another, the sheer volume of data may forbid a formally optimal analysis, requiring judicious balancing of model sophistication, approximations, and clever algorithms. Often the data bear a complex relationship to the underlying phenomenon producing them, much in the manner of inverse problems.
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