Forecasting and change point test for nonlinear heteroscedastic time series based on support vector regression

HIGHLIGHTS

• who: HsinKai Wang et al. from the Department of Applied Mathematics, Sun Yat-sen, Kaohsiung, Taiwan, Department of have published the paper: Forecasting and change point test for nonlinear heteroscedastic time series based on support vector regression, in the Journal: PLOS ONE of November/25,/2022
• what: The authors explore the change point detection problem in the SVR-ARMA-GARCH model using the residual-based CUSUM test. For this task the authors propose an alternating recursive estimation (ARE) method to improve the estimation accuracy of residuals. The aim of this paper is twofold: the first . . .
  

   

  

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