Wavelet smoothing based multivariate polynomial for anchovy catches forecasting

NIBALDO RODRIGUEZ AGURTO, Eleuterio Yañez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paprer, a multivariate polynomial (MP) combined with smoothing techniques is proposed to forecast 1-month ahead monthly anchovy catches in the north area of Chile. The anchovy catches data is smoothed by using multiscale discrete stationary wavelet transform and then appropriate is used as inputs to the MP. The MP's parameters are estimated using the penalized least square method and the performance evaluation of the proposed forecaster showed that a 98 percent of the explained variance was captured with a reduced parsimony.

Original languageEnglish
Title of host publicationCIS 2009 - 2009 International Conference on Computational Intelligence and Security
Pages38-41
Number of pages4
DOIs
StatePublished - 1 Dec 2009
Event2009 International Conference on Computational Intelligence and Security, CIS 2009 - Beijing, China
Duration: 11 Dec 200914 Dec 2009

Publication series

NameCIS 2009 - 2009 International Conference on Computational Intelligence and Security
Volume1

Conference

Conference2009 International Conference on Computational Intelligence and Security, CIS 2009
CountryChina
CityBeijing
Period11/12/0914/12/09

Keywords

  • Forecasting
  • Wavelet analysis

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