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Application of Statistical Methods of Time-Series for Estimating and Forecasting the Wheat Series in Yemen (Production and Import)
American Journal of Applied Mathematics
Volume 4, Issue 3, June 2016, Pages: 124-131
Received: Apr. 4, 2016; Accepted: Apr. 15, 2016; Published: May 4, 2016
Authors
Douaik Ahmed, The National Institute of Agronomic Research (INRA), Rabat, Morocco
Youssfi Elkettan, Department of Mathematics Faculty of Sciences, University Ibn Tofail, Kenitra, Morocco
Abdulbakee Kasem, Department of Mathematics Faculty of Sciences, University Ibn Tofail, Kenitra, Morocco
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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.
Keywords
Time Series, Wheat Crop, Forecasting, Box and Jenkins, Exponential Smoothing
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), American Journal of Applied Mathematics. Vol. 4, No. 3, 2016, pp. 124-131. doi: 10.11648/j.ajam.20160403.12
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