Bayesian analysis of running holographic Ricci dark energy

Abstract

Holographic Ricci dark energy evolving through its interaction with dark matter is a natural choice for the running vacuum energy model. We have analyzed the relative significance of two versions of this model in the light of SNIa, CMB, BAO and Hubble data sets using the method Bayesian inferences. The first one, model 1, is the running holographic Ricci dark energy (rhrde) having a constant additive term in its density form and the second is one, model 2, having no additive constant, instead the interaction of rhrde with dark matter is accounted through a phenomenological coupling term. The Bayes factor of these models in comparison with the standard $\Lambda$CDM have been obtained by calculating the likelihood of each model for four different data combinations, SNIa(307)+CMB+BAO, SNIa(307)+CMB+BAO+Hubble data, SNIa(580)+CMB+BAO and SNIa(580)+CMB+BAO+Hubble data. Suitable flat priors for the model parameters has been assumed for calculating the likelihood in both cases. Our analysis shows that, according to the Jeffreys scale, the evidence for $\Lambda$CDM against both model 1 and model 2 is very strong as the Bayes factor of both models are much less than one for all the data combinations.

arXiv comment15 pages and 7 figures

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Cited by in corpus (1)

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