Minitutorial: The Pinball Loss for Quantile Forecasts

Stephan Kolassa

Foresight: The International Journal of Applied Forecasting, 2023, issue 68, 66-67

Abstract: Kolassa writes about the usefulness of the pinball loss, "an error measure (or loss function) that has been around at least since Koenker and Bassett (1978) popularized it for quantile regression." Copyright International Institute of Forecasters, 2023

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
https://forecasters.org/foresight/bookstore/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:for:ijafaa:y:2023:i:68:p:66-67

Access Statistics for this article

More articles in Foresight: The International Journal of Applied Forecasting from International Institute of Forecasters Contact information at EDIRC.
Bibliographic data for series maintained by Michael Gilliland ().