Statistical Challenges in Modern Astronomy

TL;DR

This paper reviews the current state and future challenges of statistical methods in astronomy, emphasizing the need for advanced tools to address complex data analysis problems in modern observational research.

Contribution

It highlights the gap between statistical methodology and astronomical research, and outlines new challenges posed by the Virtual Observatory for astrostatistics.

Findings

Astronomy faces complex statistical problems requiring advanced methods.

Recent resurgence in astrostatistical research addresses these challenges.

Future infrastructure and research directions are outlined for the coming decade.

Abstract

Despite centuries of close association, statistics and astronomy are surprisingly distant today. Most observational astronomical research relies on an inadequate toolbox of methodological tools. Yet the needs are substantial: astronomy encounters sophisticated problems involving sampling theory, survival analysis, multivariate classification and analysis, time series analysis, wavelet analysis, spatial point processes, nonlinear regression, bootstrap resampling and model selection. We review the recent resurgence of astrostatistical research, and outline new challenges raised by the emerging Virtual Observatory. Our essay ends with a list of research challenges and infrastructure for astrostatistics in the coming decade.