SLANTS: Sequential Adaptive Nonlinear Modeling of Time Series

Dynamic Adaptive Partitioning for Nonlinear Time Series Dynamic Adaptive Partitioning for Nonlinear Time Series

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 a...

Dynamic Adaptive Partitioning for Nonlinear Time Series

Dynamic Adaptive Partitioning for Nonlinear Time Series

We propose a dynamic adaptive partitioning scheme for nonparametric analysis of stationary nonlinear time series. It yields estimates of the whole probability distribution of the underlying process. 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 pa...

Sequential recurrent connectionist algorithms for time series modeling of nonlinear dynamical systems

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Modeling and prediction of time-series of monthly copper prices

One of the main tasks to analyze and design a mining system is predicting the behavior exhibited by prices in the future. In this paper, the applications of different prediction methods are evaluated in econometrics and financial management fields, such as ARIMA, TGARCH, and stochastic differential equations, for the time-series of monthly copper prices. Moreover, the performance of these metho...