22 citations · 63 across the 13 of their papers we have counts for
14 papers
Spatial modelling of COVID-19 incident cases using Richards' curve: an application to the Italian regions
Marco Mingione, Pierfrancesco Alaimo Di Loro, Alessio Farcomeni +4
We introduce an extended generalised logistic growth model for discrete outcomes, in which a network structure can be specified to deal with spatial dependence and time dependence…
Nowcasting COVID-19 incidence indicators during the Italian first outbreak
Pierfrancesco Alaimo Di Loro, Fabio Divino, Alessio Farcomeni +4
A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal is motivated by real-time monitoring and short-term forecas…
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…
An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian Regions
Alessio Farcomeni, Antonello Maruotti, Fabio Divino +2
The availability of intensive care beds during the Covid-19 epidemic is crucial to guarantee the best possible treatment to severely affected patients. In this work we show a simpl…
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…