Accounting for Selection Bias Using Simulations: A General Method and an Application to Millimeter-wavelength Surveys
AffiliationUniv Arizona, Steward Observ, Dept Astron
KeywordsAstronomy data modeling
Radio source catalogs
MetadataShow full item record
PublisherIOP PUBLISHING LTD
CitationGralla, M. B., & Marriage, T. A. (2020). Accounting for selection bias using simulations: A general method and an application to millimeter-wavelength surveys. The Astrophysical Journal, 893(2), 103.
Rights© 2020. The American Astronomical Society. All rights reserved.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractWe have developed a new Bayesian method to correct the flux densities of astronomical sources. The hybrid method combines a simulated likelihood to model survey selection together with an analytic source-count-based prior. The simulated likelihood captures the effect of complicated selection methods, such as multi-frequency filtering or imposed restrictions on recovered sample properties (e.g., color cuts). Simulations are also able to capture unanticipated sources of uncertainty. In this way, the method enables a broader application of Bayesian techniques. Use of an analytic prior allows variation of assumed source count models without re-simulating the likelihood. We present the method along with a detailed description of an application to real survey data from the Atacama Cosmology Telescope.
VersionFinal published version