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Bayesian cross validation for gravitational-wave searches in pulsar-timing array data

Wang, Haochen and Taylor, Stephen R. and Vallisneri, Michele (2019) Bayesian cross validation for gravitational-wave searches in pulsar-timing array data. Monthly Notices of the Royal Astronomical Society, 487 (3). pp. 3644-3649. ISSN 0035-8711. https://resolver.caltech.edu/CaltechAUTHORS:20190815-140748905

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Abstract

Gravitational-wave data analysis demands sophisticated statistical noise models in a bid to extract highly obscured signals from data. In Bayesian model comparison, we choose among a landscape of models by comparing their marginal likelihoods. However, this computation is numerically fraught and can be sensitive to arbitrary choices in the specification of parameter priors. In Bayesian cross validation, we characterize the fit and predictive power of a model by computing the Bayesian posterior of its parameters in a training data set, and then use that posterior to compute the averaged likelihood of a different testing data set. The resulting cross-validation scores are straightforward to compute; they are insensitive to prior tuning; and they penalize unnecessarily complex models that overfit the training data at the expense of predictive performance. In this article, we discuss cross validation in the context of pulsar-timing-array data analysis, and we exemplify its application to simulated pulsar data (where it successfully selects the correct spectral index of a stochastic gravitational-wave background), and to a pulsar data set from the NANOGrav 11-yr release (where it convincingly favours a model that represents a transient feature in the interstellar medium). We argue that cross validation offers a promising alternative to Bayesian model comparison, and we discuss its use for gravitational-wave detection, by selecting or refuting models that include a gravitational-wave component.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1093/mnras/stz1537DOIArticle
https://arxiv.org/abs/1904.05355arXivDiscussion Paper
ORCID:
AuthorORCID
Taylor, Stephen R.0000-0003-0264-1453
Vallisneri, Michele0000-0002-4162-0033
Additional Information:© 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). Accepted 2019 May 28. Received 2019 May 24; in original form 2019 April 10. Published: 04 June 2019. We thank Joseph Simon and Michael Lam for discussions regarding the dispersion-measure variation of PSR J1713+0747. This research was performed in part using the Zwicky computer cluster at Caltech supported by the National Science Foundation under MRI-R2 award No. PHY0960291 and by the Sherman Fairchild Foundation. Portions of this research were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. This work was supported in part by National Science Foundation Grant No. PHYS-1066293 and by the hospitality of the Aspen Center for Physics. MV was supported by the Jet Propulsion Laboratory RTD program. SRT was supported by the NANOGrav National Science Foundation Physics Frontier Center, award number 1430284. Parts of this work were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration. Copyright 2019 California Institute of Technology. Government sponsorship acknowledged.
Group:TAPIR
Funders:
Funding AgencyGrant Number
NSFPHY-0960291
Sherman Fairchild FoundationUNSPECIFIED
NASA/JPL/CaltechUNSPECIFIED
NSFPHYS-1066293
JPL Research and Technology Development FundUNSPECIFIED
NSFPHY-1430284
Subject Keywords:gravitational waves – methods: statistical – pulsars: general
Issue or Number:3
Record Number:CaltechAUTHORS:20190815-140748905
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190815-140748905
Official Citation:Haochen Wang, Stephen R Taylor, Michele Vallisneri, Bayesian cross validation for gravitational-wave searches in pulsar-timing array data, Monthly Notices of the Royal Astronomical Society, Volume 487, Issue 3, August 2019, Pages 3644–3649, https://doi.org/10.1093/mnras/stz1537
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:97929
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:15 Aug 2019 21:28
Last Modified:09 Mar 2020 13:19

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