An Algorithm of Nonparametric Quantile Regression.
Conditional quantile
Extreme value distribution
Generalized Pareto distribution
Kernel estimation
Linear programming
Nonparametric quantile regression
Journal
Journal of statistical theory and practice
ISSN: 1559-8608
Titre abrégé: J Stat Theory Pract
Pays: United States
ID NLM: 101513487
Informations de publication
Date de publication:
2023
2023
Historique:
accepted:
25
01
2023
medline:
5
4
2023
entrez:
4
4
2023
pubmed:
5
4
2023
Statut:
ppublish
Résumé
Extreme events, such as earthquakes, tsunamis, and market crashes, can have substantial impact on social and ecological systems. Quantile regression can be used for predicting these extreme events, making it an important problem that has applications in many fields. Estimating high conditional quantiles is a difficult problem. Regular linear quantile regression uses an
Identifiants
pubmed: 37013135
doi: 10.1007/s42519-023-00325-8
pii: 325
pmc: PMC10057703
doi:
Types de publication
Journal Article
Langues
eng
Pagination
32Informations de copyright
© Crown 2023.
Déclaration de conflit d'intérêts
Conflict of interestThe authors declare no conflict of interest.
Références
J Am Coll Cardiol. 2018 May 15;71(19):e127-e248
pubmed: 29146535
Lancet Respir Med. 2020 May;8(5):506-517
pubmed: 32272080