  We use Gaussian processes in combination with MCMC method to place
constraints on cosmological parameters of three dark energy models including
flat and curved FRW and Bianchi type I spacetimes. To do so, we use recently
compiled 36 measurements of the Hubble parameter $H(z)$ in the redshifts
intermediate $0.07\leqslant z \leqslant 2.36$. Moreover, we use these models to
estimate the redshift of the deceleration-acceleration transition. We consider
two 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 NUTS
sampler which is an extension of Hamiltonian Monte Carlo algorithm to generate
MCMC chains for parameters of dark energy models. To compare the considered
cosmologies, we perform Akaike information criterion (AIC) and Bayes factor
($\Psi$). In general, when we compared our results with 9 years WMAP as well as
Planck 2015 Collaboration, we found that Bianchi type I model is slightly fits
better to the observational Hubble data with respect to the non-flat FRW model.
