Abstract
The autodependogram is a graphical device recently proposed in the literature to analyze autodependencies.
It is defined computing the classical Pearson chi-square statistics of independence at various lags in order to point out the presence lag-depedencies.
This paper proposes an improvement of this diagram obtained by substituting the chi-square statistics with an estimator of the Kullback–Leibler divergence between the bivariate density of two delayed variables and the product of their marginal distributions.
A simulation study, on well-established time series models, shows that this new autodependogram is more powerful than the previous one.
An application to a well-known financial time series is also shown.
Original language | English |
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Pages (from-to) | 2574-2594 |
Number of pages | 21 |
Journal | Journal of Applied Statistics |
Volume | (43)14 |
DOIs | |
Publication status | Published - 2016 |
Keywords
- Kullback–Leibler divergence
- Nonlinear time series