Handley, W;
Lemos, P;
(2019)
Quantifying dimensionality: Bayesian cosmological model complexities.
Physical Review D
, 100
(2)
, Article 023512. 10.1103/PhysRevD.100.023512.
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Abstract
We demonstrate a measure for the effective number of parameters constrained by a posterior distribution in the context of cosmology. In the same way that the mean of the Shannon information (i.e., the Kullback-Leibler divergence) provides a measure of the strength of constraint between prior and posterior, we show that the variance of the Shannon information gives a measure of dimensionality of constraint. We examine this quantity in a cosmological context, applying it to likelihoods derived from the cosmic microwave background, large-scale structure and supernovae data. We show that this measure of Bayesian model dimensionality compares favorably both analytically and numerically in a cosmological context with the existing measure of model complexity used in the literature.
| Type: | Article |
|---|---|
| Title: | Quantifying dimensionality: Bayesian cosmological model complexities |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1103/PhysRevD.100.023512 |
| Publisher version: | https://doi.org/10.1103/PhysRevD.100.023512 |
| Language: | English |
| Additional information: | This is the published version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10078669 |
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