Wavelet Smoothing Based FAR Model for Monthly Tuna Catches Forecasting

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.