Status on bidimensional dark energy parameterizations using SNe Ia JLA
  and BAO datasets
  Using current observations forecast type Ia supernovae (SNe Ia) Joint
Lightcurve Analysis (JLA) and baryon acoustic oscillations (BAO), in this paper
we investigate six bidimensional dark energy parameterisations in order to
explore which has more constraining power. Our results indicate that for
parameterisations that contain $z^2$-terms, the tension ($\sigma$-distance)
between these datasets seems to be reduced and their behaviour are $<$1$\sigma$
compatible with $\Lambda$CDM. Also, the results obtained by performing their
Bayesian evidence show a striking evidence in favour of the $\Lambda$CDM model,
but only one parameterisation can be distinguish by around $1\%$ from the other
models when the combination of datasets are considered.
