175 citations · 245 across the 15 of their papers we have counts for
12 papers · 1 filter
Generalized propensity score weighting for functional causal inference framework
Simone Ciardulli, Nicole Fontana, Simone Vantini +1
Estimating causal effects in observational studies requires adjustment for confounding, a task that becomes challenging when the exposure is a function observed over a continuous d…
Local inference for functional data on manifold domains using permutation tests
Niels Lundtorp Olsen, Alessia Pini, Simone Vantini
Pini and Vantini (2017) introduced the interval-wise testing procedure which performs local inference for functional data defined on an interval domain, where the output is an adju…
funLOCI: a local clustering algorithm for functional data
Jacopo Di Iorio, Simone Vantini
Nowadays, more and more problems are dealing with data with one infinite continuous dimension: functional data. In this paper, we introduce the funLOCI algorithm which allows to id…
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…
Adaptive Smoothing Spline Estimator for the Function-on-Function Linear Regression Model
Fabio Centofanti, Antonio Lepore, Alessandra Menafoglio +2
In this paper, we propose an adaptive smoothing spline (AdaSS) estimator for the function-on-function linear regression model where each value of the response, at any domain point,…
Ridge regression with adaptive additive rectangles and other piecewise functional templates
Edoardo Belli, Simone Vantini
We propose an -based penalization algorithm for functional linear regression models, where the coefficient function is shrunk towards a data-driven shape template , which…
Smooth Lasso Estimator for the Function-on-Function Linear Regression Model
Fabio Centofanti, Matteo Fontana, Antonio Lepore +1
A new estimator, named S-LASSO, is proposed for the coefficient function of the Function-on-Function linear regression model. The S-LASSO estimator is shown to be able to increase…
Global Sensitivity and Domain-Selective Testing for Functional-Valued Responses: An Application to Climate Economy Models
Matteo Fontana, Massimo Tavoni, Simone Vantini
Understanding the dynamics and evolution of climate change and associated uncertainties is key for designing robust policy actions. Computer models are key tools in this scientific…
False Discovery Rate for Functional Data
Niels Lundtorp Olsen, Alessia Pini, Simone Vantini
Since Benjamini and Hochberg introduced false discovery rate (FDR) in their seminal paper, this has become a very popular approach to the multiple comparisons problem. An increasin…