Dynamic Adaptive Partitioning for Nonlinear Time Series Dynamic Adaptive Partitioning for Nonlinear Time Series
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چکیده
We propose a dynamic adaptive partitioning scheme for nonparametric analysis of stationary nonlinear time series with values in IR d (d 1). We use information from past values to construct adaptive partitioning in a dynamic fashion which is then diierent from the more common static schemes in the regression setup. The idea of dynamic partitioning is novel. We make it constructive by proposing an approach based on quantization of the data and adaptively modelling partition cells with a parsimonious Markov chain. The methodology is formulated in terms of a model class, the so-called quantized variable length Markov chains (QVLMC). We discuss when and why such a QVLMC partitioning scheme is in some sort natural and canonical. We explore asymptotic properties and give some numerical results which reeect the nite sample behavior.
منابع مشابه
Dynamic Adaptive Partitioning for Nonlinear Time Series
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تاریخ انتشار 1998