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PhysRevD.82.103533.pdf (274.27 kB)

Application of Bayesian model averaging to measurements of the primordial power spectrum

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posted on 2023-06-08, 08:29 authored by David Parkinson, Andrew R Liddle
Cosmological parameter uncertainties are often stated assuming a particular model, neglecting the model uncertainty, even when Bayesian model selection is unable to identify a conclusive best model. Bayesian model averaging is a method for assessing parameter uncertainties in situations where there is also uncertainty in the underlying model. We apply model averaging to the estimation of the parameters associated with the primordial power spectra of curvature and tensor perturbations. We use CosmoNest and MultiNest to compute the model evidences and posteriors, using cosmic microwave data from WMAP, ACBAR, BOOMERanG, and CBI, plus large-scale structure data from the SDSS DR7. We find that the model-averaged 95% credible interval for the spectral index using all of the data is 0.940

History

Publication status

  • Published

File Version

  • Published version

Journal

Physical Review D

ISSN

15507998

Issue

10

Volume

82

Department affiliated with

  • Physics and Astronomy Publications

Notes

Article number 103533

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2012-02-06

First Open Access (FOA) Date

2016-03-22

First Compliant Deposit (FCD) Date

2016-11-10

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