# A Bayesian interpretation of inconsistency measures in cosmology

@article{Lin2021ABI, title={A Bayesian interpretation of inconsistency measures in cosmology}, author={Weikang Lin and Mustapha Ishak}, journal={Journal of Cosmology and Astroparticle Physics}, year={2021}, volume={2021} }

Measures of inconsistency and tension between datasets have become an essential part of cosmological analyses. It is important to accurately evaluate the significance of such tensions when present. We propose here a Bayesian interpretation of inconsistency measures that can extract information about physical inconsistencies in the presence of data scatter. This new framework is based on the conditional probability distribution of the level of physical inconsistency given the obtained value of…

## 4 Citations

### Testing the consistency between cosmological data: the impact of spatial curvature and the dark energy EoS

- PhysicsJournal of Cosmology and Astroparticle Physics
- 2021

The results of joint analyses of available cosmological data have motivated an important debate about a possible detection of a non-zero spatial curvature. If confirmed, such a result would imply a…

### Gamma-Ray Burst Constraints on Cosmological Models from the Improved Amati Correlation

- PhysicsThe Astrophysical Journal
- 2022

An improved Amati correlation was constructed in ApJ 931 (2022) 50 by us recently. In this paper, we further study constraints on the ΛCDM and wCDM models from the gamma-ray bursts (GRBs)…

### Optical and X-ray GRB Fundamental Planes as cosmological distance indicators

- PhysicsMonthly Notices of the Royal Astronomical Society
- 2022

Gamma-ray bursts (GRBs), can be employed as standardized candles, extending the distance ladder beyond Type Ia supernovae (SNe Ia, z = 2.26). We standardize GRBs using the three-dimensional (3D)…

### Non-Gaussian estimates of tensions in cosmological parameters

- Computer SciencePhysical Review D
- 2021

Two families of scalable algorithms are developed that allow for efficiently and reliably estimate the level of agreement and disagreement on parameter determinations from different experiments, fully taking into account non-Gaussianities in the parameter posteriors.

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