Bayesian jackknife tests with a small number of subsets: application to HERA 21 cm power spectrum upper limits

Michael J. Wilensky, Fraser Kennedy, Philip Bull, Joshua S. Dillon, Zara Abdurashidova, Tyrone Adams, James E. Aguirre, Paul Alexander, Zaki S. Ali, Rushelle Baartman, Yanga Balfour, Adam P. Beardsley, Gianni Bernardi, Tashalee S. Billings, Judd D. Bowman, Richard F. Bradley, Jacob Burba, Steven Carey, Chris L. Carilli, Carina ChengDavid R. Deboer, Eloy De Lera Acedo, Matt Dexter, Nico Eksteen, John Ely, Aaron Ewall-Wice, Nicolas Fagnoni, Randall Fritz, Steven R. Furlanetto, Kingsley Gale-Sides, Brian Glendenning, Deepthi Gorthi, Bradley Greig, Jasper Grobbelaar, Ziyaad Halday, Bryna J. Hazelton, Jacqueline N. Hewitt, Jack Hickish, Daniel C. Jacobs, Austin Julius, MacCalvin Kariseb, Nicholas S. Kern, Joshua Kerrigan, Piyanat Kittiwisit, Saul A. Kohn, Matthew Kolopanis, Adam Lanman, Paul La Plante, Adrian Liu, Anita Loots, David Harold Edward Macmahon, Lourence Malan, Cresshim Malgas, Keith Malgas, Bradley Marero, Zachary E. Martinot, Andrei Mesinger, Mathakane Molewa, Miguel F. Morales, Tshegofalang Mosiane, Steven G. Murray, Abraham R. Neben, Bojan Nikolic, Hans Nuwegeld, Aaron R. Parsons, Nipanjana Patra, Samantha Pieterse, Nima Razavi-Ghods, James Robnett, Kathryn Rosie, Peter Sims, Hilton Swarts, Nithyanandan Thyagarajan, Pieter Van Wyngaarden, Peter K.G. Williams, Haoxuan Zheng

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We present a Bayesian jackknife test for assessing the probability that a data set contains biased subsets, and, if so, which of the subsets are likely to be biased. The test can be used to assess the presence and likely source of statistical tension between different measurements of the same quantities in an automated manner. Under certain broadly applicable assumptions, the test is analytically tractable. We also provide an open-source code, chiborg, that performs both analytic and numerical computations of the test on general Gaussian-distributed data. After exploring the information theoretical aspects of the test and its performance with an array of simulations, we apply it to data from the Hydrogen Epoch of Reionization Array (HERA) to assess whether different sub-seasons of observing can justifiably be combined to produce a deeper 21 cm power spectrum upper limit. We find that, with a handful of exceptions, the HERA data in question are statistically consistent and this decision is justified. We conclude by pointing out the wide applicability of this test, including to CMB experiments and the H0 tension.

Original languageEnglish (US)
Pages (from-to)6041-6058
Number of pages18
JournalMonthly Notices of the Royal Astronomical Society
Volume518
Issue number4
DOIs
StatePublished - Feb 1 2023

Keywords

  • cosmology: observations
  • dark ages, reionization, first stars
  • methods: data analysis
  • methods: statistical
  • software: data analysis

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

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