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Application of Statistical Methods of Time-Series for Estimating and Forecasting the Wheat Series in Yemen (Production and Import)

Received: 4 April 2016    Accepted: 15 April 2016    Published: 4 May 2016
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Abstract

Due to the importance of the wheat crop which represents 90% of the grain consumed, In this papers, we compared between the following statistical methods : Box and Jenkins model, exponential smoothing models (with trend and without seasonal) and Simple regression for estimating and forecasting to two time series of wheat(production and import). We reached to the following results: 1. Brown exponential smoothing model for modeling the imported wheat series. 2. ARIMA (1, 1, 1) model for modeling the product wheat series. For the wheat crop, the ratio of production to consumption is expected to reach 6.3% in 2015 and continues to decline even up to 5.4% in 2020. This means that the problem of food security well be worse in Yemen.

Published in American Journal of Applied Mathematics (Volume 4, Issue 3)
DOI 10.11648/j.ajam.20160403.12
Page(s) 124-131
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Time Series, Wheat Crop, Forecasting, Box and Jenkins, Exponential Smoothing

References
[1] Peter J. Brockwell et Richard A Davis (2002), Introduction to Time Series and Forecasting, Springer.
[2] Philippe Marier, cours Prévision de la demande, Consortium de Recherche Université Laval.
[3] Lahoussaine Baamal, (2012), Cours d’analyse des Séries Chronologiques. Université Ibn Tofail,Kénitra.
[4] E. Ostertagova, O. Ostertag, The Simple Exponential Smoothing Model, http://www.researchgate.net/publication/256088917
[5] Rodolphe Palm, (2007), Etude des séries chronologiques par méthodes de lissage, Faculté Universitaire des Sciences agronomiques, Unité de Statistique, Informatique et Mathématique appliquées, Belgique.
[6] Bary Adnan Majed, (2002), Statistical forecasting methods-1, Université du Roi Saoud.
[7] Ruey S. Tsay, (2005), Analysis of financial time series, Wiley,Hoboken, New Jersey.
[8] Lahoussaine Baamal, (2012), Cours de Prévision par la Méthodologie de Box et Jenkins. Université Ibn Tofail.
[9] IBM, (2011), IBM SPSS Forecasting.
[10] A.Douaik, (1991), Prévision des rendements agricoles par les méthodes de lissage exponentiel. Mémoire ingénieur, Faculté des Sciences Agronomique de Gembloux, Belgique.
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  • APA Style

    Douaik Ahmed, Youssfi Elkettan, Abdulbakee Kasem. (2016). Application of Statistical Methods of Time-Series for Estimating and Forecasting the Wheat Series in Yemen (Production and Import). American Journal of Applied Mathematics, 4(3), 124-131. https://doi.org/10.11648/j.ajam.20160403.12

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    ACS Style

    Douaik Ahmed; Youssfi Elkettan; Abdulbakee Kasem. Application of Statistical Methods of Time-Series for Estimating and Forecasting the Wheat Series in Yemen (Production and Import). Am. J. Appl. Math. 2016, 4(3), 124-131. doi: 10.11648/j.ajam.20160403.12

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    AMA Style

    Douaik Ahmed, Youssfi Elkettan, Abdulbakee Kasem. Application of Statistical Methods of Time-Series for Estimating and Forecasting the Wheat Series in Yemen (Production and Import). Am J Appl Math. 2016;4(3):124-131. doi: 10.11648/j.ajam.20160403.12

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  • @article{10.11648/j.ajam.20160403.12,
      author = {Douaik Ahmed and Youssfi Elkettan and Abdulbakee Kasem},
      title = {Application of Statistical Methods of Time-Series for Estimating and Forecasting the Wheat Series in Yemen (Production and Import)},
      journal = {American Journal of Applied Mathematics},
      volume = {4},
      number = {3},
      pages = {124-131},
      doi = {10.11648/j.ajam.20160403.12},
      url = {https://doi.org/10.11648/j.ajam.20160403.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajam.20160403.12},
      abstract = {Due to the importance of the wheat crop which represents 90% of the grain consumed, In this papers, we compared between the following statistical methods : Box and Jenkins model, exponential smoothing models (with trend and without seasonal) and Simple regression for estimating and forecasting to two time series of wheat(production and import). We reached to the following results: 1. Brown exponential smoothing model for modeling the imported wheat series. 2. ARIMA (1, 1, 1) model for modeling the product wheat series. For the wheat crop, the ratio of production to consumption is expected to reach 6.3% in 2015 and continues to decline even up to 5.4% in 2020. This means that the problem of food security well be worse in Yemen.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - Application of Statistical Methods of Time-Series for Estimating and Forecasting the Wheat Series in Yemen (Production and Import)
    AU  - Douaik Ahmed
    AU  - Youssfi Elkettan
    AU  - Abdulbakee Kasem
    Y1  - 2016/05/04
    PY  - 2016
    N1  - https://doi.org/10.11648/j.ajam.20160403.12
    DO  - 10.11648/j.ajam.20160403.12
    T2  - American Journal of Applied Mathematics
    JF  - American Journal of Applied Mathematics
    JO  - American Journal of Applied Mathematics
    SP  - 124
    EP  - 131
    PB  - Science Publishing Group
    SN  - 2330-006X
    UR  - https://doi.org/10.11648/j.ajam.20160403.12
    AB  - Due to the importance of the wheat crop which represents 90% of the grain consumed, In this papers, we compared between the following statistical methods : Box and Jenkins model, exponential smoothing models (with trend and without seasonal) and Simple regression for estimating and forecasting to two time series of wheat(production and import). We reached to the following results: 1. Brown exponential smoothing model for modeling the imported wheat series. 2. ARIMA (1, 1, 1) model for modeling the product wheat series. For the wheat crop, the ratio of production to consumption is expected to reach 6.3% in 2015 and continues to decline even up to 5.4% in 2020. This means that the problem of food security well be worse in Yemen.
    VL  - 4
    IS  - 3
    ER  - 

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Author Information
  • The National Institute of Agronomic Research (INRA), Rabat, Morocco

  • Department of Mathematics Faculty of Sciences, University Ibn Tofail, Kenitra, Morocco

  • Department of Mathematics Faculty of Sciences, University Ibn Tofail, Kenitra, Morocco

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