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Identification of product life cycle models by autoregression–moving average models and Groebner’s bases

  • Semenychev, Valery

    ()

    (Samara Academy of State and Municipal Management)

  • Kurkin, Eugen

    ()

    (Samara Academy of State and Municipal Management)

  • Semenychev , Eugene

    ()

    (Samara Academy of State and Municipal Management)

Registered author(s):

    The authors offer the analytical models of product life cycle and the approach towards their classification based on the models of autoregression–moving average and using the Groebner bases for solving the normal systems of non-linear polynomial equations, received after using the least-squares method. The characteristics of modeling and forecasting fidelity have been also elaborated, concerning the sales data for cars, data for oil production, as well as interest of Google users towards cell phone models and guide-books edition.

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    File URL: http://pe.cemi.rssi.ru/pe_2012_1_122-137.pdf
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    Article provided by Publishing House "SINERGIA PRESS" in its journal Applied Econometrics.

    Volume (Year): 25 (2012)
    Issue (Month): 1 ()
    Pages: 122-137

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    Handle: RePEc:ris:apltrx:0167
    Contact details of provider: Web page: http://appliedeconometrics.cemi.rssi.ru/

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    1. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
    2. Beveridge, Stephen & Nelson, Charles R., 1981. "A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the `business cycle'," Journal of Monetary Economics, Elsevier, vol. 7(2), pages 151-174.
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