4 papers
Kernel-Based Nonparametric Tests For Shape Constraints
Rohan Sen
We propose a kernel-based nonparametric framework for mean-variance optimization that enables inference on economically motivated shape constraints in finance, including positivity…
Fast Empirical Scenarios
Michael Multerer, Paul Schneider, Rohan Sen
We seek to extract a small number of representative scenarios from large panel data that are consistent with sample moments. Among two novel algorithms, the first identifies scenar…
Probabilistic energy forecasting through quantile regression in reproducing kernel Hilbert spaces
Luca Pernigo, Rohan Sen, Davide Baroli
Accurate energy demand forecasting is crucial for sustainable and resilient energy development. To meet the Net Zero Representative Concentration Pathways (RCP) scenario in t…
Observation-specific explanations through scattered data approximation
Valentina Ghidini, Michael Multerer, Jacopo Quizi +1
This work introduces the definition of observation-specific explanations to assign a score to each data point proportional to its importance in the definition of the prediction pro…