Nonlinear Time Series Models: An Application on Amount of Water Flow of Blue Nile River Measured at Eldaim Station - Ahmed Orsud, Merdi; Younis Ibrahim, Bassam (Gezira Journal of Engineering and Applied Sciences, 2009)
This  paper  had  undertaken nonlinear time series modelling and  in  particular, discussed  wavelet  smoothing  technique to decompose the time  series into a wavelet smoothed component and  a random  component. The  random  component  was then modelled  by an  appropriate  linear ARIMA process or diagonal pure bilinear process. Before  smoothing  technique  was applied, flow data was tested for  linearity  and  then filtered. By investigating the plot of the third cumulant, it was found that diagonal pure bilinear process of order two was the best for the data sets under study. diagonal Pure  bilinear of order  two  model was fitted to time series data set  based  on  the  mean  daily  Blue Nile River flow variable at Eldaim  Station,  (during the period  January 2005 to December 2006)   using   wavelet   smoothing   technique.  A   simulation technique was performed to find the appropriateness of the model by comparing  its  performance  with  the actual time series data.            The     wavelet    smoothing    technique   demonstrated   an attractive   technique  to model such a time series data.