29 citations · 53 across the 15 of their papers we have counts for
16 papers
Environmental Risk Assessment via Nonhomogeneous Hidden Semi-Markov Models with Penalized Vector Auto-Regression
Marco Mingione, Pierfrancesco Alaimo Di Loro, Francesco Lagona +1
Motivated by the study of pollution trends in the city of Bergen, we introduce a flexible statistical framework for modeling multivariate air pollution data via a nonhomogeneous Hi…
Monitoring the West-Nile virus outbreaks in Italy using open-access data
Marco Mingione, Francesco Branda, Antonello Maruotti +2
This paper introduces a comprehensive and original database on West Nile virus (WNV) outbreaks that have occurred in Italy from September 2012 to November 2022. We have digitized b…
Parsimonious Hidden Markov Models for Matrix-Variate Longitudinal Data
Salvatore D. Tomarchio, Antonio Punzo, Antonello Maruotti
Hidden Markov models (HMMs) have been extensively used in the univariate and multivariate literature. However, there has been an increased interest in the analysis of matrix-variat…
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…
A two-part finite mixture quantile regression model for semi-continuous longitudinal data
Antonello Maruotti, Luca Merlo, Lea Petrella
This paper develops a two-part finite mixture quantile regression model for semi-continuous longitudinal data. The proposed methodology allows heterogeneity sources that influence…
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…
A copula-based multivariate hidden Markov model for modelling momentum in football
Marius Ötting, Roland Langrock, Antonello Maruotti
We investigate the potential occurrence of change points - commonly referred to as "momentum shifts" - in the dynamics of football matches. For that purpose, we model minute-by-min…
Modelling corporate defaults: A Markov-switching Poisson log-linear autoregressive model
Geir D. Berentsen, Jan Bulla, Antonello Maruotti +1
This article extends the autoregressive count time series model class by allowing for a model with regimes, that is, some of the parameters in the model depend on the state of an u…
On initial direction, orientation and discreteness in the analysis of circular variables
Gianluca Mastrantonio, Giovanna Jona Lasinio, Antonello Maruotti +1
In this paper, we propose a discrete circular distribution obtained by extending the wrapped Poisson distribution. This new distribution, the Invariant Wrapped Poisson (IWP), enjoy…
A flexible bivariate location-scale finite mixture approach to economic growth
Alessandra Marcelletti, Antonello Maruotti, Giovanni Trovato
We introduce a multivariate multidimensional mixed-effects regression model in a finite mixture framework. We relax the usual unidimensionality assumption on the random effects mul…
Bayesian Hidden Markov Modelling Using Circular-Linear General Projected Normal Distribution
Gianluca Mastrantonio, Antonello Maruotti, Giovanna Jona Lasinio
We introduce a multivariate hidden Markov model to jointly cluster time-series observations with different support, i.e. circular and linear. Relying on the general projected norma…
Handling non-ignorable dropouts in longitudinal data: A conditional model based on a latent Markov heterogeneity structure
Antonello Maruotti
We illustrate a class of conditional models for the analysis of longitudinal data suffering attrition in random effects models framework, where the subject-specific random effects…
Time-varying clustering of multivariate longitudinal observations
Antonello Maruotti, Maurizio Vichi
We propose a statistical method for clustering of multivariate longitudinal data into homogeneous groups. This method relies on a time-varying extension on the classical K-means al…
A biclustering approach to university performances: an Italian case study
Valentina Raponi, Francesca Martella, Antonello Maruotti
University evaluation is a topic of increasing concern in Italy as well as in other countries. In empirical analysis, university activities and performances are generally measured…
Multivariate Markov-Switching models and tail risk interdependence
Mauro Bernardi, Antonello Maruotti, Lea Petrella
Markov switching models are often used to analyze financial returns because of their ability to capture frequently observed stylized facts. In this paper we consider a multivariate…