37 citations · 76 across the 8 of their papers we have counts for
9 papers
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…
Mid-quantile regression for discrete responses
Marco Geraci, Alessio Farcomeni
We develop quantile regression methods for discrete responses by extending Parzen's definition of marginal mid-quantiles. As opposed to existing approaches, which are based on eith…
Quantile contours and allometric modelling for risk classification of abnormal ratios with an application to asymmetric growth-restriction in preterm infants
Marco Geraci, Nansi S. Boghossian, Alessio Farcomeni +1
We develop an approach to risk classification based on quantile contours and allometric modelling of multivariate anthropometric measurements. We propose the definition of allometr…
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…