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pro vyhledávání: '"Mingione, Marco"'
Autor:
Lagona, Francesco, Mingione, Marco
We exploit Gaussian copulas to specify a class of multivariate circular distributions and obtain parametric models for the analysis of correlated circular data. This approach provides a straightforward extension of traditional multivariate normal mod
Externí odkaz:
http://arxiv.org/abs/2406.04085
Autor:
Lagona, Francesco, Mingione, Marco
A nonhomogeneous hidden semi-Markov model is proposed to segment toroidal time series according to a finite number of latent regimes and, simultaneously, estimate the influence of time-varying covariates on the process' survival under each regime. Th
Externí odkaz:
http://arxiv.org/abs/2312.14719
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 bulletins published by the Italian National Institute of Health (ISS) t
Externí odkaz:
http://arxiv.org/abs/2306.02727
Autor:
Caruso, Gianmarco, Di Loro, Pierfrancesco Alaimo, Mingione, Marco, Tardella, Luca, Pace, Daniela Silvia, Lasinio, Giovanna Jona
In this work, the goal is to estimate the abundance of an animal population using data coming from capture-recapture surveys. We leverage the prior knowledge about the population's structure to specify a parsimonious finite mixture model tailored to
Externí odkaz:
http://arxiv.org/abs/2304.06999
Autor:
Mingione, Marco, Di Loro, Pierfrancesco Alaimo, Farcomeni, Alessio, Divino, Fabio, Lovison, Gianfranco, Lasinio, Giovanna Jona, Maruotti, Antonello
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 is dealt with using an Auto-Regressive approach. A major challenge con
Externí odkaz:
http://arxiv.org/abs/2106.05067
Autor:
Di Loro, Pierfrancesco Alaimo, Mingione, Marco, Lipsitt, Jonah, Batteate, Christina M., Jerrett, Michael, Banerjee, Sudipto
The majority of Americans fail to achieve recommended levels of physical activity, which leads to numerous preventable health problems such as diabetes, hypertension, and heart diseases. This has generated substantial interest in monitoring human act
Externí odkaz:
http://arxiv.org/abs/2101.01624
Autor:
Di Loro, Pierfrancesco Alaimo, Divino, Fabio, Farcomeni, Alessio, Lasinio, Giovanna Jona, Lovison, Gianfranco, Maruotti, Antonello, Mingione, Marco
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 forecasting of the main epidemiological indicators within the first outbreak
Externí odkaz:
http://arxiv.org/abs/2010.12679
Deep generative models are rapidly becoming a common tool for researchers and developers. However, as exhaustively shown for the family of discriminative models, the test-time inference of deep neural networks cannot be fully controlled and erroneous
Externí odkaz:
http://arxiv.org/abs/1903.02926
Akademický článek
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Autor:
Mingione, Marco, Alaimo Di Loro, Pierfrancesco, Farcomeni, Alessio, Divino, Fabio, Lovison, Gianfranco, Maruotti, Antonello, Lasinio, Giovanna Jona
Publikováno v:
In Spatial Statistics June 2022 49