Can a Bivariate AR(1) Process Model the Variability of the Inflow into Stochastic Reservoirs?
2006 (English)In: Proceeding (556) Environmental Modelling and Simulation - 2006, 2006Conference paper (Refereed)
Here we investigate the statistical evidence for a novel class of constrained bivariate AR(1) processes to capture the temporal dynamics of the maximum and minimum for the hourly/daily inflow into a stochastic reservoir. The estima tion is done using a perturbed maximum likelihood tech nique and is illustrated by an empirical example
Place, publisher, year, edition, pages
Hydrological models; autoregression; non-Gaussian time series; range modeling.
IdentifiersURN: urn:nbn:se:uu:diva-25671OAI: oai:DiVA.org:uu-25671DiVA: diva2:53445