Quantile Regression for Cross-Sectional and Time Series Data : Applications in Energy Markets Using R

by Jorge M. Uribe, Montserrat Guillen

Why and When Should Quantile Regression Be Used?- A Case of Study: Modelling Energy Markets by the Means of Quantile Regression -- Quantile Regression: A Methodological Overview -- Cross-Sectional Quantile Regression -- Time Series Quantile Regression -- Goodness of Fit in Quantile Regression Models -- Novel Approaches in Quantile Regression -- What Have We Learned from Quantile Regression? Implications for Economics and Finance -- Appendix: Programs for Quantile Regression and Implementation in R. .

MoreLess

Year of publication:	2020 ; 1st ed. 2020.
Authors:	Uribe, Jorge ; Guillén, Montserrat
Publisher:	2020.: Cham : Springer International Publishing 2020.: Cham : Imprint: Springer
Subject:	Quantilsregression \| Quantile regression \| Modellierung \| Scientific modelling \| Zeitreihenanalyse \| Time series analysis \| Schätzung \| Estimation \| Energiemarkt \| Energy market
Description of contents:	Description [swbplus.bsz-bw.de]

Extent:	1 Online-Ressource(X, 63 p. 13 illus., 7 illus. in color.)
Series:	SpringerBriefs in Finance Springer eBook Collection
Type of publication:	Book / Working Paper
Language:	English
ISBN:	978-3-030-44504-1 ; 978-3-030-44503-4 ; 978-3-030-44505-8
Other identifiers:	10.1007/978-3-030-44504-1 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012399314