Advances and Applications in Statistics
Volume 59, Issue 1, Pages 75 - 87
(November 2019) http://dx.doi.org/10.17654/AS059010075 |
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COMPARISON OF TWO REGRESSION MODELS FOR PREDICTING COTTON YIELDS IN THE LOGONE OCCIDENTAL REGION OF SOUTH CHAD
Ouchar Cherif Ali, Stéphane Metchebon Takougang Aime, Rasmane Yaro, Youssouf Pare and Blaise Some
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Abstract: In this work, we study the two regression models for cotton crop yield forecasts taking into account the factors influenced by climatic hazards in the Western Logone region of South Chad.
It is very useful to have a model of cotton crop yield forecasts, taking into account the climatic hazards in order to be able to anticipate yields. As a result, it will provide insight into crop decision-making before the season begins.
The comparative study also consists in studying the performance indices of each model before choosing the model that will be implemented in the form of the flexible and ergonomic computer application.
This work is based on observational data collected over a period of three decades. The data from the first two decades are used for model learning and the data from the third decade are used to validate the models with performance indices. After validation testing, we confirm the efficiency and improvement of the adjustment quality of the regression model on the main components as well as the quality of the forecasts obtained. Differences between observed and expected yields are due to the effects and hazards of climate change. |
Keywords and phrases: climate change, yield, regression components, statistics, linear regression.
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