Hurdle and Generalized Additive Models

We show that the baryonic fraction and the rate of ionizing photons appear to have a larger impact on fesc than previously thought. A naive univariate analysis of the same problem would suggest smaller effects for these properties and a much larger impact for the specific star formation rate, which is lessened after accounting for other galaxy properties and non-linearities in the statistical model.

Representativeness in Machine Learning applications for photometric redshifts

We present two galaxy catalogues built to enable a more demanding and realistic test of photo-z methods. We demonstrate the potential of these catalogues by submitting them to the scrutiny of different photo-z methods, including machine learning (ML) and template fitting approaches. Our catalogues represent the first controlled environment allowing a straightforward implementation of such tests.

Hierarchical Bayesian Models

We developed a hierarchical Bayesian model to investigate how the presence of Seyfert activity relates to their environment. In elliptical galaxies, our analysis indicates a strong correlation of Seyfert-AGN activity with the cluster centric distance, and a weaker correlation with the mass of the host. In spiral galaxies these trends do not appear, suggesting that the link between Seyfert activity and the properties of spiral galaxies are independent of the environment.