A Note on the Bivariate ACER Method
نویسنده
چکیده
The paper focuses on the extension of the ACER method for prediction of extreme value statistics to the case of bivariate time series. Using the ACER method it is possible to provide an estimate of the exact extreme value distribution of a univariate time series. This is obtained by introducing a cascade of conditioning approximations to the exact extreme value distribution. When this cascade has converged, an estimate of the exact distribution has been obtained. In this paper it will be shown how the univariate ACER method can be extended in a natural way to also cover the case of bivariate data. In fact, the ACER method can in principle be extended to multivariate time series of any dimension. However, the requirements to the requisite statistical analyses would severely hamper a practical implementation for higher dimensional cases.
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