Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-04T05:09:43.072Z Has data issue: false hasContentIssue false
  • English
  • Français

Searching for bias and correlations in a Bayesian way - Example: SN Ia data

Published online by Cambridge University Press:  01 July 2015

Caroline Heneka ,
Alexandre Posada ,
Valerio Marra  and
Luca Amendola
Caroline Heneka
Affiliation:
Dark Cosmology Centre, Niels Bohr Institute, University of Copenhagen, Juliane Maries Vej 30, DK-2100 Copenhagen, Denmark email: [email protected]
Alexandre Posada
Affiliation:
Centre de Physique théorique, Université d'Aix-Marseille, Campus de Luminy Case 907, 13288 Marseille cedex 9, France
Valerio Marra
Affiliation:
Instituto de Física, Universidade Federal do Rio de Janeiro CEP 21941-972, Rio de Janeiro, RJ, Brazil
Luca Amendola
Affiliation:
Institut für Theoretische Physik, Universität Heidelberg, Philosophenweg 16, D-69120 Heidelberg, Germany
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

A range of Bayesian tools has become widely used in cosmological data treatment and parameter inference (see Kunz et al.2007, Trotta 2008, Amendola et al.2013). With increasingly big datasets and higher precision, tools that enable us to further enhance the accuracy of our measurements gain importance. Here we present an approach based on internal robustness, introduced in Amendola et al. (2013) and adopted in Heneka et al. (2014), to identify biased subsets of data and hidden correlation in a model independent way.

Keywords

methods: statisticalcosmology: cosmological parametersstars: supernovae: general
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 10 , Symposium S306: Statistical Challenges in 21st Century Cosmology , May 2014 , pp. 19 - 21
Copyright
Copyright © International Astronomical Union 2015 

References

Ade, P., et al. (Planck Collaboration) 2013, 1303.5083Google Scholar
Amendola, L., Marra, V., & Quartin, M. 2013, MNRAS, 430, 1867CrossRefGoogle Scholar
Heneka, C., Marra, V., & Amendola, L. 2014, MNRAS, 439, 1855Google Scholar
Kunz, M., Bassett, B. A., & Hlozek, R. 2007, Phys. Rev. D, 75, 103508Google Scholar
Suzuki, N. 2012, ApJ, 746, 85Google Scholar
Trotta, R. 2008, Contemp. Phys., 49, 71Google Scholar