Current constraints on anisotropic and isotropic dark energy models

We use Gaussian processes in combination with the Markov chain Monte Carlo method to place constraints on the cosmological parameters of five dark energy models including flat and curved XCDM, flat and curved ΛCDM, and Bianchi type-I spacetime. To do so, we use recently compiled 36 measurements of the Hubble parameter $H(z)$ in the redshifts intermediate 0.07≤z≤2.36. Moreover, we use these models to estimate the redshift of the deceleration-acceleration transition. We consider two Gaussian priors for the current value of the Hubble constant, namely, H₀=73±1.74(68±2.8) km/s/Mpc to investigate the effect of the assumed H₀ on our parameter estimations. For statistical analysis, we use the NUTS sampler, which is an extension of the Hamiltonian Monte Carlo algorithm to generate the Markov chain Monte Carlo chains for parameters of the dark energy models. To compare the considered cosmologies, we perform the Akaike information criterion and Bayes factor (Ψ). In general, when we compared our results to the other results such as those obtained from WMAP 9-year and Planck 2015 Collaboration, we found that the Bianchi type-I model fits slightly better the observational Hubble data with respect to the nonflat, XCDM, and ΛCDM models.