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We use Gaussian processes in combination with MCMC method to placeconstraints on cosmological parameters of three dark energy models includingflat and curved FRW and Bianchi type I spacetimes. To do so, we use recentlycompiled 36 measurements of the Hubble parameter $H(z)$ in the redshiftsintermediate $0.07\leqslant z \leqslant 2.36$. Moreover, we use these models toestimate the redshift of the deceleration-acceleration transition. We considertwo Gaussian priors for current value of the Hubble constant i.e$H_{0}=73\pm1.74 (68\pm 2.8)$ km/s/Mpc to investigate the effect of the assumed$H_{0}$ on our parameters estimations. For statistical analysis we use NUTSsampler which is an extension of Hamiltonian Monte Carlo algorithm to generateMCMC chains for parameters of dark energy models. To compare the consideredcosmologies, we perform Akaike information criterion (AIC) and Bayes factor($\Psi$). In general, when we compared our results with 9 years WMAP as well asPlanck 2015 Collaboration, we found that Bianchi type I model is slightly fitsbetter to the observational Hubble data with respect to the non-flat FRW model.

Current Constraints on Anisotropic and Isotropic Dark Energy Models