Multiple streamflow time series modeling using VAR–MGARCH approach

• Published in: Stochastic environmental research and risk assessment Vol. 33; no. 2; pp. 407 - 425
• Main Authors: Fathian, Farshad, Fakheri-Fard, Ahmad, Ouarda, T. B. M. J., Dinpashoh, Yagob, Mousavi Nadoushani, S. Saeid
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2019; Springer Nature B.V
• Subjects: Aquatic Pollution; Arches; Bivariate analysis; Chemistry and Earth Sciences; Computational Intelligence; Computer Science; Computer simulation; Covariance; Dependence; Earth and Environmental Science; Earth Sciences; Econometrics; Economic models; Environment; Experiments; Hydrologic data; Hydrologic models; Hydrology; Math. Appl. in Environmental Science; Modelling; Original Paper; Physics; Probability Theory and Stochastic Processes; Regression analysis; Statistics for Engineering; Stream discharge; Stream flow; Time series; Variance; Waste Water Technology; Water Management; Water Pollution Control; Diagonal VECH; Multiple streamflow time series; Conditional variance–covariance; Assessment criteria; Conditional correlation; VAR

Multivariate time series modeling approaches are known as valuable methods for simulating and forecasting the temporal evolution of hydroclimatic variables. These approaches are also useful for modeling the temporal dependence and cross-dependence between variables and sites. Although multiple linea...