Algorithms of the Copula Fit to the Nonlinear Processes in the Utility Industry

Procedia Computer Science 2017
Andrejs Matvejevs, Jegors Fjodorovs, Anatoliy Malyarenko

Our research studies the construction and estimation of copula-based semi parametric Markov model for the processes, which involved in water flows in the hydro plants. As a rule analyzing the dependence structure of stationary time series regressive models defined by invariant marginal distributions and copula functions that capture the temporal dependence of the processes is considered. This permits to separate out the temporal dependence (such as tail dependence) from the marginal behavior (such as fat tails) of a time series. Dealing with utility company data we have found the best copula describing data - Gumbel copula. As a result constructed algorithm was used for an imitation of low probability events (in a hydro power industry) and predictions.

Atslēgas vārdi
Copula; Diffusion processes; Time series; Semi parametric regressions
DOI
10.1016/j.procs.2017.01.174
Hipersaite
https://www.sciencedirect.com/science/article/pii/S1877050917301758?via%3Dihub

Matvejevs, A., Fjodorovs, J., Malyarenko, A. Algorithms of the Copula Fit to the Nonlinear Processes in the Utility Industry. Procedia Computer Science, 2017, Vol. 104, 572.-577.lpp. ISSN 1877-0509. Pieejams: doi:10.1016/j.procs.2017.01.174

Publikācijas valoda
English (en)