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Nonlinear Correlograms and Partial Autocorrelograms

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journal contribution
posted on 07.06.2017, 00:26 by Anderson, Heather M., Vahid, Farshid
This paper proposes neural network based measures of predictability in conditional mean, and then uses them to construct nonlinear analogues to autocorrelograms and partial autocorrelograms. In contrast to other measures of nonlinear dependence that rely on nonparametric estimation of densities or multivariate integration, our autocorrelograms are simple to calculate and appear to work well in relatively small samples.


Year of first publication



Department of Econometrics and Business Statistics