Variance decompositions of nonlinear time series using stochastic simulation and sensitivity analysis |
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Authors: | T J Harris and W Yu |
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Institution: | (1) Institute for theProtection and the Security of the Citizen, Ispra, Italy; |
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Abstract: | In this paper, A variance decomposition approach to quantify the effects of endogenous and exogenous variables for nonlinear
time series models is developed. This decomposition is taken temporally with respect to the source of variation. The methodology
uses Monte Carlo methods to affect the variance decomposition using the ANOVA-like procedures proposed in Archer et al. (J.
Stat. Comput. Simul. 58:99–120, 1997), Sobol’ (Math. Model. 2:112–118, 1990). The results of this paper can be used in investment problems, biomathematics and control theory, where nonlinear time series
with multiple inputs are encountered. |
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Keywords: | |
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