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Oscillatory components in the bell-shaped curves of the product life cycle modeling tool

Author

Listed:
  • Semenychev, Valery

    (Samara Academy of State and Municipal Management)

  • Kurkin, Eugene

    (Samara Academy of State and Municipal Management)

  • Semenychev, Eugene

    (Samara Academy of State and Municipal Management)

  • Danilova, Anastasia

    (Samara Academy of State and Municipal Management)

Abstract

Product life cycle models set consisting of bell-shape trend models and five oscillating components structures was suggested. Genetic algorithm type method with ARMA model construction to allocate frequencies was submitted to model parameters identification. The examples of oil, gas and coal mining real samples modeling and forecasting with all proposed models were considered.

Suggested Citation

  • Semenychev, Valery & Kurkin, Eugene & Semenychev, Eugene & Danilova, Anastasia, 2014. "Oscillatory components in the bell-shaped curves of the product life cycle modeling tool," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 111-123.
  • Handle: RePEc:ris:apltrx:0232
    as

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    References listed on IDEAS

    as
    1. Eugen Ursu & Kamil Feridun Turkman, 2012. "Periodic autoregressive model identification using genetic algorithms," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(3), pages 398-405, May.
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    3. Patzek, Tadeusz W. & Croft, Gregory D., 2010. "A global coal production forecast with multi-Hubbert cycle analysis," Energy, Elsevier, vol. 35(8), pages 3109-3122.
    4. Brandt, Adam R., 2007. "Testing Hubbert," Energy Policy, Elsevier, vol. 35(5), pages 3074-3088, May.
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    More about this item

    Keywords

    product life cycle; bell-shape trend; oscillating component; genetic algorithm; ARMA model; oil; gas; coal; mining;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels

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