Skip to Main Content (Press Enter)

Logo UNIBG
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Persone
  • Pubblicazioni
  • Strutture
  • Attività
  • Competenze

UNI-FIND
Logo UNIBG

|

UNI-FIND

unibg.it
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Persone
  • Pubblicazioni
  • Strutture
  • Attività
  • Competenze
  1. Pubblicazioni

Bayesian functional emulation of CO2 emissions on future climate change scenarios

Articolo
Data di Pubblicazione:
2023
Citazione:
(2023). Bayesian functional emulation of CO2 emissions on future climate change scenarios [journal article - articolo]. In ENVIRONMETRICS. Retrieved from https://hdl.handle.net/10446/295986
Abstract:
We propose a statistical emulator for a climate-economy deterministic integrated assessment model ensemble, based on a functional regression framework. Inference on the unknown parameters is carried out through a mixed effects hierarchical model using a fully Bayesian framework with a prior distribution on the vector of all parameters. We also suggest an autoregressive parameterization of the covariance matrix of the error, with matching marginal prior. In this way, we allow for a functional framework for the discretized output of the simulators that allows their time continuous evaluation.
Tipologia CRIS:
1.1.01 Articoli/Saggi in rivista - Journal Articles/Essays
Keywords:
Bayesian statistics; functional regression; hierarchical modeling; mixed effects model; uncertainty quantification;
Elenco autori:
Aiello, Luca; Fontana, Matteo; Guglielmi, Alessandra
Autori di Ateneo:
AIELLO Luca
Link alla scheda completa:
https://aisberg.unibg.it/handle/10446/295986
Link al Full Text:
https://aisberg.unibg.it/retrieve/handle/10446/295986/786198/Environmetrics%20-%202023%20-%20Aiello%20-%20Bayesian%20functional%20emulation%20of%20CO2%20emissions%20on%20future%20climate%20change%20scenarios.pdf
Pubblicato in:
ENVIRONMETRICS
Journal
  • Ricerca

Ricerca

Settori


Settore STAT-01/A - Statistica
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 25.6.1.0