Wavelet smoothing based FAR model for monthly tuna catches foercasting

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

Abstract

In this paper, the aim is to apply a functional autoregressive (FAR) model combined with wavelet smoothing analysis for monthly bigeye tuna catches forecasting in the equatorial Indian ocean. The raw monthly tuna catches data is smoothed by using discrete stationary wavelet transform and then appropriate is used as inputs to the FAR model. We find that the proposed forecasting strategy achieves 97% of the explained variance with reduced parsimony and high accuracy.

Original languageEnglish
Title of host publication2009 2nd International Conference on Future Information Technology and Management Engineering, FITME 2009
Pages389-391
Number of pages3
DOIs
StatePublished - 1 Dec 2009
Event2009 2nd International Conference on Future Information Technology and Management Engineering, FITME 2009 - Sanya, China
Duration: 13 Dec 200914 Dec 2009

Publication series

Name2009 2nd International Conference on Future Information Technology and Management Engineering, FITME 2009

Conference

Conference2009 2nd International Conference on Future Information Technology and Management Engineering, FITME 2009
CountryChina
CitySanya
Period13/12/0914/12/09

Keywords

  • Forecasting
  • Wavelet smooting

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