Lag space estimation in time series modelling

Cyril Goutte

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    Abstract

    The purpose of this article is to investigate some techniques for finding the relevant lag-space, i.e. input information, for time series modelling. This is an important aspect of time series modelling, as it conditions the design of the model through the regressor vector a.k.a. the input layer in a neural network. We give a rough description of the problem, insist on the concept of generalisation, and propose a generalisation-based method. We compare it to a non-parametric test, and carry out experiments, both on the well-known Henon map, and on a real data set
    Original languageEnglish
    Title of host publication1997 Intl. Conference on Acoustics, Speech, and Signal Processing
    Place of PublicationPiscataway,New Jersey
    PublisherIEEE
    Publication date1997
    Pages3313-3316
    ISBN (Print)0-8186-7919-0
    DOIs
    Publication statusPublished - 1997
    Event1997 Intl. Conference on Acoustics, Speech, and Signal Processing -
    Duration: 1 Jan 1997 → …

    Conference

    Conference1997 Intl. Conference on Acoustics, Speech, and Signal Processing
    Period01/01/1997 → …

    Bibliographical note

    Copyright: 1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

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