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bsj-3425
A comparison among Different Methods for Estimating Regression Parameters with Autocorrelation Problem under Exponentially Distributed Error
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Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of cigarettes according to the US Federal Trade Commission.

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Publication Date
Sun Sep 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The reality of Taxation in Iraq and Aspect of it’s Development
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This research is considered a simple attempt and effort which is it first and last target is to point at the procedures of the taxes account that aims to reduce the taxes from the persons and give free to the person who estimates the tax to practice what comes from the competent authorities to describe the person who estimates the tax and not an accountant who practice the accountant procedures which are imposed on him by the annual terms from higher administrations , So he can not evaluate   state of the person who pay the tax , and he might be dissatisfied with his job , because his role can’t  be activated from the general foundation taxes.

And so , this research includes four fields:-

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Publication Date
Sat Sep 01 2018
Journal Name
Polyhedron
Novel dichloro (bis {2-[1-(4-methylphenyl)-1H-1, 2, 3-triazol-4-yl-κN3] pyridine-κN}) metal (II) coordination compounds of seven transition metals (Mn, Fe, Co, Ni, Cu, Zn and Cd)
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