  We theoretically quantify the impact of observational errors on the recovered
age for stars in MS and RGB phases. We adopted Teff, [Fe/H], Delta_nu and
nu_max as observational constraints. Artificial stars were sampled from a
reference isochrone and subjected to random perturbation to simulate
observational errors. Their ages were then recovered by means of a MCMC
approach. The differences between the recovered and true ages were modelled
against the errors in the observables by means of linear models and projection
pursuit regression models. From linear models we find that no age error source
dominates. For MS the most important error source is Teff. An offset of 75 K
accounts for an underestimation of the stellar age from 0.4 to 0.6 Gyr for
initial and terminal MS. An error of 2.5% in nu_max accounted for about -0.3
Gyr. A 0.1 dex error in [Fe/H] resulted particularly important only at the end
of the MS, with an age error of -0.4 Gyr. For the RGB phase the dominant source
of uncertainty is nu_max, causing an underestimation of about 0.6 Gyr; the
offset in the effective temperature and Delta_nu caused respectively an
underestimation and overestimation of 0.3 Gyr. We find that the inference from
the linear model is a good proxy for that from projection pursuit regression
models, so that linear models can be safely used thanks to its broader
generalizability. Finally, we explored the impact on age estimates of adding
the luminosity to the other observational constraints. We assumed - for
computational reasons - a 2.5% error in luminosity, much lower than the average
error in the Gaia DR2 catalogue. Even in this optimistic case, the luminosity
does not increase precision of age estimates. Moreover, the luminosity resulted
as a major contributor to the variability in the estimated ages, accounting for
an error of about -0.3 Gyr in the explored evolutionary phases.
