Abstract: Rwanda agricultural is today characterized by low productivity due to some factors inputs. Maize production in the country is becoming increasingly important in Rwanda agriculture market. So the purpose of this research is then to determine the variance covariance relationship between variables which main factors could be identified and subsequently give more investment weight for maize quality and volume production development. These variables include organic fertilizer, cultivated area, improved seed, average temperature and annual rainfall
The analysis of data done by using an orthogonal factor model to describe and determine the variance covariance relationship among many variables in terms of a few underlying called latent factors which can be not observed.
The finding give the answer to our objectives. We found that there is a linear relationship between variables where annual rainfall indicates a negative correlation effect on production of maize. But other variables as average temperature, improved seed, organic fertilizer and cultivated area have positive correlation with production of maize. Next, we found that the improved seed variable shows a high correlation than other variables this suggests that is the most likely increase production of maize in Rwanda. Finally, the variance covariance relationship between factors was determined by estimating loading using rotation method. We found that in oblique rotation the variances explained by the first and second factors are greater than orthogonal rotation. In the oblique cases, the common factors are correlated and display a covariance variance value which is seems acceptable.
Keywords: Covariance Relationship, Orthogonal Factor Model, A Orthogonal Factor Model for the Agriculture market.
Title: Orthogonal Factor Model for the Factors Affecting the Production of Maize in Rwanda
Author: Iradukunda M. Innocent, Dr. Mung'atu Joseph, Dr. Ndengo Marcel
International Journal of Social Science and Humanities Research
ISSN 2348-3156 (Print), ISSN 2348-3164 (online)
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