FARIMA with stable innovations model of Great Salt Lake elevation time series

نویسندگان

  • Hu Sheng
  • Yangquan Chen
چکیده

Great Salt Lake (GSL) is the largest salt lake in the western hemisphere, the fourthlargest terminal lake in the world. The elevation of GSL has critical effect on the people who live nearby and their properties. It is crucial to build an exact model of GSL elevation time series in order to predict the GSL elevation precisely. Although some models, such as ARIMA or FARIMA (fractional auto-regressive integrated moving average), GARCH (generalized auto-regressive conditional heteroskedasticity) and FIGARCH (fractional integral generalized auto-regressive conditional heteroskedasticity) have been proposed to characterize the variation of GSL elevation, which have been unsatisfactory. Therefore, it became a key point to build a more appropriate model of GSL elevation time series. In this paper a newmodel based on FARIMA with stable innovations is applied to analyze the data and predict the future elevation levels. From the analysis we can see that the new model can characterize GSL elevation time series more accurately. The new model will be beneficial to predict GSL elevation more precisely. & 2010 Elsevier B.V. All rights reserved.

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عنوان ژورنال:
  • Signal Processing

دوره 91  شماره 

صفحات  -

تاریخ انتشار 2011