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Abstract
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Article Information:
Research on Recursive Grouping Data Barycenter Method and its Application
Ji-Lin Zhang
Corresponding Author: Ji-Lin Zhang
Submitted: November 28, 2011
Accepted: January 04, 2012
Published: June 01, 2012 |
Abstract:
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A new and useful parameter estimating method for econometric dynamic model is proposed in this
paper. Moreover, a new forecasting method is also proposed in this paper based on it. These methods could deal
with the fitting and forecasting of economy dynamic model and could greatly decrease the forecasting errors
result from the singularity of the real data. Moreover, the strict hypothetical conditions in least squares method
were not necessary in the method presented in this paper, which overcome the shortcomings of least squares
method and expanded the application of data barycentre method. The new methods are applied to Chinese steel
consumption forecasting based on the historic data. It is shown that the result of fitting and forecasting was
satisfactory. From the comparison between new forecasting method and least squares method, we could
conclude that the fitting and forecasting results using data barycentre method was more stable than that using
least squares regression forecasting method, and the computation of data barycentre forecasting method was
simpler than that of least squares method. As a result, the data barycentre method was convenient to use in
technical economy.
Key words: Data barycentre, parameter estimation, steel consumption forecasting, triangle recursive, , ,
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Cite this Reference:
Ji-Lin Zhang, . Research on Recursive Grouping Data Barycenter Method and its Application. Research Journal of Applied Sciences, Engineering and Technology, (11): 1484-1487.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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