Abstract
Exponential smooth transition autoregressive (ESTAR) is a family of parametric nonlinear time-series models capable of capturing the non-Gaussian characteristics of the time-series along with cyclical fluctuations. The present study is based on the time-series data on oilsardine landings from Kerala during the period 1961 to 2008. The parameters of the model were estimated by genetic algorithm (GA). From the analysis of data it was concluded that ESTAR model fitted through GA has performed better than ARIMA model.
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