This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.
In this paper, three approximate methods namely the Bernoulli, the Bernstein, and the shifted Legendre polynomials operational matrices are presented to solve two important nonlinear ordinary differential equations that appeared in engineering and applied science. The Riccati and the Darcy-Brinkman-Forchheimer moment equations are solved and the approximate solutions are obtained. The methods are summarized by converting the nonlinear differential equations into a nonlinear system of algebraic equations that is solved using Mathematica®12. The efficiency of these methods was investigated by calculating the root mean square error (RMS) and the maximum error remainder (𝑀𝐸𝑅n) and it was found that the accuracy increases with increasi
... Show MoreThe childhood stage is considered the most important stage of all the stages through
the human being’s life. In this stage the human being will be more affected by the various
factors that surround him/her. The first five years of his/her life leave a great impact not only
on the human being personality, but also on his/her whole life. Therefore, it is worthwhile tobe concerned with and focus at the raising up and the teaching of the child during the
childhood stage.
The mission of raising up children in this era - the era of globalization and information
bursting or news flooding – has become a very difficult or even an impossible mission.
Furthermore, not only in the Arabic world, but also all over the world, t
The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma
... Show MoreSemiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use
... Show MoreIn this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in
The pretreatment process can be considered one of the important processes in wastewater treatment, especially coagulation process to decrease the strength of many pollutants. This paper focused on using powdered date seeds as natural coagulant in addition to chemical coagulants (alum and ferric chloride) to find the optimum dosage of each coagulant that makes efficient removal of turbidity and chemical oxygen demand (COD) from domestic wastewater as a pretreatment process, then finding the optimum combined dosages of date seeds with alum, date seeds with ferric chloride that make efficient removal for both pollutants. Concerning turbidity, the optimum dosage for date seeds, alum and ferric chloride were 40 mg/l (79%), 70
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