A Finite Mixture GARCH Approach with EM Algorithm for Energy Forecasting Applications

A Finite Mixture GARCH Approach with EM Algorithm for Energy Forecasting Applications

Enhancing forecasting performance in terms of both the expected mean value and variance has been a critical challenging issue for energy industry. In this paper, the novel methodology of finite mixture Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) approach with Expectation–Maximi...

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Bibliographic Details
Main Authors: Yang Zhang, Yidong Peng, Xiuli Qu, Jing Shi, Ergin Erdem
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Energies
Subjects:
finite mixture
GARCH
EM algorithm
forecasting
wind speed
wind energy
Online Access:https://www.mdpi.com/1996-1073/14/9/2352

Internet

https://www.mdpi.com/1996-1073/14/9/2352

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