Effect of low anisotropy on cosmological models by using supernova data
  By using the supernovae type Ia data we study influence of the anisotropy
(although low) on the evolution of the universe and compare ${\Lambda}$CDM
model with 6 representative parametrizations of the recent Hubble expansion
history $H(z)$. To compare these models we use the the maximum likelihood
method for find that the best fit dynamical $\omega(z)$ and $q(z)$ obtained
from the SNIa dataset. In particular we find the best fit value of $\Lambda$CDM
model $(\Omega_{\sigma_0}= 0.013$, $\chi^2_{min}=197.56)$. The analysis shows
that by considering the anisotropy, it leads to more best fit parameters in all
models (except of SCDM) with SNIa data. We also use two statistical tests such
as the usual $\chi^2_{min}/dof$ and p-test to compare different dark energy
models. According to both statistical tests and considering anisotropy, the
linear parametrization model that is providing the best fit to $\Lambda$CDM
model.
