Authors
Martin Kunz, Renée Hlozek, Bruce A Bassett, Mathew Smith, James Newling, Melvin Varughese
Publication date
2013
Journal
Astrostatistical Challenges for the New Astronomy
Pages
63-86
Publisher
Springer New York
Description
We present Bayesian Estimation Appliedto Multiple Species (BEAMS), an algorithm designed to deal with parameter estimation when using contaminated data. We introduce the algorithm and demonstrate how it works with the help of a Gaussian simulation. We then apply it to supernova data from the Sloan Digital Sky Survey (SDSS), showing how the resulting confidence contours of the cosmo-logical parameters shrink significantly.
Total citations
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Scholar articles
M Kunz, R Hlozek, BA Bassett, M Smith, J Newling… - Astrostatistical Challenges for the New Astronomy, 2013