12 citations · 19 across the 5 of their papers we have counts for
5 papers
K-Models: a Flexible and Interpretable Method for Ordinal Clustering with Application to Antigen-Antibody Interaction Profiles
Giulia Patanè, Alessandra Menafoglio, Alexander Krauth +4
Existing clustering methods for functional data often prioritize partitioning accuracy over interpretability, making it challenging to extract meaningful insights when the data-gen…
Functional-Ordinal Canonical Correlation Analysis With Application to Data from Optical Sensors
Giulia Patanè, Federica Nicolussi, Alexander Krauth +4
We address the problem of predicting a target ordinal variable based on observable features consisting of functional profiles. This problem is crucial, especially in decision-makin…
Modelling provincial Covid-19 epidemic data in Italy using an adjusted time-dependent SIRD model
Luisa Ferrari, Giuseppe Gerardi, Giancarlo Manzi +4
In this paper we develop a predictive model for the spread of COVID-19 infection at a provincial (i.e. EU NUTS-3) level in Italy by using official data from the Italian Ministry of…
COVID-Pro in Italy: a dashboard for a province-based analysis
Luisa Ferrari, Giuseppe Gerardi, Giancarlo Manzi +3
This paper presents an dashboard developed to analyse the outbreak of the Covid-19 infection in Italy considering daily NUTS-3 data on positive cases provided by the Italian Minist…
Context-specific independencies for ordinal variables in chain regression models
Federica Nicolussi, Manuela Cazzaro
In this work we handle with categorical (ordinal) variables and we focus on the (in)dependence relationship under the marginal, conditional and context-specific perspective. If the…