Using the Generalized Partial Linear Regression Model to Determine Climatic Factor Effect on Dust Storms in Baghdad Governorate

Laith Fadhil S. H, Auday Taha R, Waleed Mohammed Elaibi


The phenomenon of dust that occurs in Iraq is one of the phenomena that cannot be completely controlled or partially processed in a short time. It also works to know how some climatic factors such as the average wind speed, relative humidity, atmospheric pressure above sea level, and the maximum temperature which represent explanatory (independent) variables , respectively. The effects on the number of occurrences of dust storms represent the adopted variable (Y) in Baghdad Governorate for the period from 2008 to mid-2013. The researchers used the Generalized Partial Linear Regression Model (GPLRM) consist of fourteen models, after determining the best link function for each model. Then we compared these models to determine the best model that represents this data with the best representation using the Akaike information criterion (AIC), the Schwartz information criterion (BIC), and the determination Coefficient criterion . We also used the program (i- xplore) in the calculation, and we have concluded that the best model is the model in which the variable  relative humidity and  the maximum temperature in the parametric part, i.e., linear and stable. On the other hand, the variable  average wind speed and the variable  atmospheric pressure above sea level are non-parametric and their behavior is non-linear and unstable. The researchers consider that Baghdad Governorate suffers from this negative phenomenon as well as in general in Iraq. Besides, the effect of the variable  relative humidity is a decreasingly negative effect, while the effect of the variable  maximum temperature, it is an increasingly positive effect.


generalized partial linear regression model; parametric model; non-parametric model; link function; dust storms.

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