2 citations · 2 across the 3 of their papers we have counts for
5 papers · 1 filter
Directional quantile classifiers
Alessio Farcomeni, Marco Geraci, Cinzia Viroli
We introduce classifiers based on directional quantiles. We derive theoretical results for selecting optimal quantile levels given a direction, and, conversely, an optimal directio…
Letter to the Editor
Marco Geraci
Galarza, Lachos and Bandyopadhyay (2017) have recently proposed a method of estimating linear quantile mixed models (Geraci and Bottai, 2014) based on a Monte Carlo EM algorithm. T…
Additive quantile regression for clustered data with an application to children's physical activity
Marco Geraci
Additive models are flexible regression tools that handle linear as well as nonlinear terms. The latter are typically modelled via smoothing splines. Additive mixed models extend a…
Mixed-effects models using the normal and the Laplace distributions: A convolution scheme for applied research
Marco Geraci
In statistical applications, the normal and the Laplace distributions are often contrasted: the former as a standard tool of analysis, the latter as its robust counterpart. I discu…
A novel quantile-based decomposition of the indirect effect in mediation analysis with an application to infant mortality in the US population
Marco Geraci, Alessandra Mattei
In mediation analysis, the effect of an exposure (or treatment) on an outcome variable is decomposed into two components: a direct effect, which pertains to an immediate influence…