25 citations · 43 across the 6 of their papers we have counts for
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Conformal Prediction Bands for Two-Dimensional Functional Time Series
Niccolò Ajroldi, Jacopo Diquigiovanni, Matteo Fontana +1
Time evolving surfaces can be modeled as two-dimensional Functional time series, exploiting the tools of Functional data analysis. Leveraging this approach, a forecasting framework…
conformalInference.multi and conformalInference.fd: Twin Packages for Conformal Prediction
Paolo Vergottini, Matteo Fontana, Jacopo Diquigiovanni +2
Building on top of a regression model, Conformal Prediction methods produce distribution free prediction sets, requiring only i.i.d. data. While R packages implementing such method…
Distribution-Free Prediction Bands for Multivariate Functional Time Series: an Application to the Italian Gas Market
Jacopo Diquigiovanni, Matteo Fontana, Simone Vantini
Uncertainty quantification in forecasting represents a topic of great importance in energy trading, as understanding the status of the energy market would enable traders to directl…
Conformal Prediction Bands for Multivariate Functional Data
Jacopo Diquigiovanni, Matteo Fontana, Simone Vantini
Motivated by the pressing request of methods able to create prediction sets in a general regression framework for a multivariate functional response and pushed by new methodologica…
On the dependence in football match outcomes: traditional model assumptions and an alternative proposal
Marco Petretta, Lorenzo Schiavon, Jacopo Diquigiovanni
The approaches routinely used to model the outcomes of football matches are characterised by strong assumptions about the dependence between the number of goals scored by the two c…
The Importance of Being a Band: Finite-Sample Exact Distribution-Free Prediction Sets for Functional Data
Jacopo Diquigiovanni, Matteo Fontana, Simone Vantini
Functional Data Analysis represents a field of growing interest in statistics. Despite several studies have been proposed leading to fundamental results, the problem of obtaining v…