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Flexible and dynamic modeling of dependencies via copulas

Boekbijdrage - Boekhoofdstuk Conferentiebijdrage

© Springer International Publishing Switzerland 2015. In this chapter we first review recent developments in the use of copulas for studying dependence structures between variables. We discuss and illustrate the concepts of unconditional and conditional copulas and association measures, in a bivariate setting. Statistical inference for conditional and unconditional copulas is discussed, in various modeling settings. Modeling the dynamics in a dependence structure between time series is of particular interest. For this we present a semiparametric approach using local polynomial approximation for the dynamic time parameter function. Throughout the chapter we provide some illustrative examples. The use of the proposed dynamical modeling approach is demonstrated in the analysis and forecast of wind speed data.
Boek: MODELING AND STOCHASTIC LEARNING FOR FORECASTING IN HIGH DIMENSIONS
Pagina's: 117 - 146
ISBN:978-3-319-18731-0
Jaar van publicatie:2015
BOF-keylabel:ja
IOF-keylabel:ja
Authors from:Higher Education