article

Finding the embedding dimension and variable dependencies in time series

Authors:

Hong Pi,

Carsten PetersonAuthors Info & Claims

Neural Computation, Volume 6, Issue 3

Pages 509 - 520

https://doi.org/10.1162/neco.1994.6.3.509

Published: 01 May 1994 Publication History

Abstract

We present a general method, the δ-test, which establishes functional dependencies given a sequence of measurements. The approach is based on calculating conditional probabilities from vector component distances. Imposing the requirement of continuity of the underlying function, the obtained values of the conditional probabilities carry information on the embedding dimension and variable dependencies. The power of the method is illustrated on synthetic time-series with different time-lag dependencies and noise levels and on the sunspot data. The virtue of the method for preprocessing data in the context of feedforward neural networks is demonstrated. Also, its applicability for tracking residual errors in output units is stressed.

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Digital Library

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Neural Computation Volume 6, Issue 3

May 1994

218 pages

ISSN:0899-7667

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MIT Press

Cambridge, MA, United States

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Published: 01 May 1994

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Liébana-Cabanillas FHerrera LGuillén A(2016)Variable selection for payment in social networksComputers in Human Behavior10.1016/j.chb.2015.10.02256:C(45-55)Online publication date: 1-Mar-2016
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