Shape-constrained uncertainty quantification in unfolding steeply falling elementary particle spectra

DOI10.1214/17-AOAS1053zbMath1380.62274arXiv1512.00905OpenAlexW2963696825MaRDI QIDQ1684243

Philip B. Stark, Mikael Kuusela

Publication date: 8 December 2017

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1512.00905

zbMATH Keywords

semi-infinite programmingFenchel dualityhigh energy physicsLarge Hadron ColliderPoisson inverse problemfinite-sample coveragenonparametric inferences

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Applications of statistics to physics (62P35)

Related Items (2)

Convergence and Error Propagation Results on a Linear Iterative Unfolding Method ⋮ Objective Frequentist Uncertainty Quantification for Atmospheric \(\mathrm{CO}_2\) Retrievals

This page was built for publication: Shape-constrained uncertainty quantification in unfolding steeply falling elementary particle spectra