A comparison of frequentist and Bayesian inference: searching for low-frequency p modes and g modes in Sun-as-a-star data

BROOMHALL, A.-M., CHAPLIN, W. J., ELSWORTH, Y., APPOURCHAUX, T. and NEW, R. (2010). A comparison of frequentist and Bayesian inference: searching for low-frequency p modes and g modes in Sun-as-a-star data. Monthly Notices of the Royal Astronomical Society, 406 (2), 767-781.

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Abstract

We describe and use two different statistical approaches to try and detect low-frequency solar oscillations in Sun-as-a-star data: a frequentist approach and a Bayesian approach. We have used frequentist statistics to search contemporaneous Sun-as-a-star data for coincident, statistically prominent features. However, we find that this approach leads to numerous false detections. We have also used Bayesian statistics to search for evidence of low-frequency p modes and g modes in Sun-as-a-star data. We describe how Bayesian statistics can be used to search near-contemporaneous data for coincident prominent features. Near-contemporaneous data were used to circumvent the difficulties in deriving probabilities that occur when common noise is present in the data. We find that the Bayesian approach, which is reliant on the assumptions made when determining the posterior probability, leads to significantly fewer false detections and those that are observed can be discredited using a priori knowledge. Therefore, we have more confidence in the mode candidates found with Bayesian statistics.

Item Type:	Article
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Materials and Engineering Research Institute > Advanced Coatings and Composites Research Centre > Nanotechnology Centre for PVD Research
Identification Number:	https://doi.org/10.1111/j.1365-2966.2010.16743.x
Page Range:	767-781
Depositing User:	Ann Betterton
Date Deposited:	25 Nov 2010 16:07
Last Modified:	19 Mar 2021 00:45
URI:	https://shura.shu.ac.uk/id/eprint/2747

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