The research dealt with a comparative study between some semi-parametric estimation methods to the Partial linear Single Index Model using simulation. There are two approaches to model estimation two-stage procedure and MADE to estimate this model. Simulations were used to study the finite sample performance of estimating methods based on different Single Index models, error variances, and different sample sizes , and the mean average squared errors were used as a comparison criterion between the methods were used. The results showed a preference for the two-stage procedure depending on all the cases that were used

The childhood period includes nursery period is the most period that the child wants to discover and knowledge and that we see it in daily and normal activity that he does it. And after creating  the science aspects  and growth it by children and that is one of goals the Education and this goal is requested a style education includes a corrective scientific aspects and creating them and getting them by experience that getting it by visits many places of nurseries and meeting some of teachers and search about the program working and application it and notes a problem  that summarized that is not found a science program used by teacher to teach the science aspects for children that realized her goals and needs to gro

Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

The research demonstrates new species of the games by applying separation axioms via  sets, where the relationships between the various species that were specified and the strategy of winning and losing to any one of the players, and their relationship with the concepts of separation axioms via  sets have been studied.

Air pollution is one of the complex problems plaguing the environment at the present time
as a result of many liberation of gases, vapors and fumes of fuels and chemicals resulting
from industrial activities . It should be noted that there are some elements of the heavy
(Heavy Metals), including toxic in the air, with different concentrations in the air depending
on the nature of the area, for example be in rural areas is lower than in cities or industrial
areas as measured parts million (ppm ) or parts per billion (ppb). Some of these important
elements in the physiological processes and enzymatic organisms but become toxic and
Qatlhand-increase Tercisahaan the permissible limits Bhave nature ,The air contaminant

The recent development in statistics has made statistical distributions the focus of researchers in the process of compensating for some distribution parameters with fixed values and obtaining a new distribution, in this study, the distribution of Kumaraswamy was studied from the constant distributions of the two parameters. The characteristics of the distribution were discussed through the presentation of the probability density function (p.d.f), the cumulative distribution function (c.d.f.), the ratio of r, the reliability function and the hazard function. The parameters of the Kumaraswamy distribution were estimated using MLE, ME, LSEE by using the simulation method for different sampling sizes and using preli

Heterocyclic systems, which are essential in medicinal chemistry due to their promising cytotoxic activity, are one of the most important families of organic molecules found in nature or produced in the laboratory. As a result of coupling N-(4-nitrophenyl)-3-oxo-butanamide (3) using thiourea, indole-3-carboxaldehyde, or piperonal, the pyrimidine derivatives (5a and 5b) were produced. Furthermore, pyrimidine 9 was synthesized by reacting thiophene-2-carboxaldehyde with ethyl cyanoacetate and urea with potassium carbonate as a catalyst. The chalcones 11a and 11b were synthesized by reacting equal molar quantities of 1-naphthaldehy

Air pollution is one of the complex problems plaguing the environment at the present time
as a result of many liberation of gases, vapors and fumes of fuels and chemicals resulting
from industrial activities . It should be noted that there are some elements of the heavy (Heavy
Metals), including toxic in the air, with different concentrations in the air depending on the
nature of the area, for example be in rural areas is lower than in cities or industrial areas as
measured parts million (ppm ) or parts per billion (ppb). Some of these important elements in
the physiological processes and enzymatic organisms but become toxic and Qatlhand-increase
Tercisahaan the permissible limits Bhave nature ,The air contaminant co

The analysis of the classic principal components are sensitive to the outliers where they are calculated from the characteristic values and characteristic vectors of correlation matrix or variance Non-Robust, which yields an incorrect results in the case of these data contains the outliers values. In order to treat this problem, we resort to use the robust methods where there are many robust methods Will be touched to some of them.

   The robust measurement estimators include the measurement of direct robust estimators for characteristic values by using characteristic vectors without relying on robust estimators for the   variance and covariance matrices. Also the analysis of the princ