Our scientists Arabs old efforts in achieving texts that led to the foundations of general
rules they have set for this work in accordance with the systematic context is based on the
study, analysis and precision in dealing with this work, which became the basis for each
investigator to the present day, which was to them careful consideration manuscripts and
work to be closer to the image by its author, so produced their efforts in this area several
books provided the technical wizards of this science, which did not leave a gap in which only
gave her treatments and suggestions each and every one of the point made by and gave her
what produced the expertise in this direction in accordance with the formulations
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This search in the virtues of the daughter of the Prophet Muhammad, to read on their boards want to recount loving and faithful), as stated in the introduction to the author, Abdullah Bin Ibrahim Al-Mirghani (D. 1207 H.) to give reasons in writing the manuscript, which was of an introduction and three chapters and a conclusion was the first in the door thanks to the great lady and on her birthday and her marriage and her death and subsequent events and the third in her them prayers and then the finale which was in love with the Prophet and calling for God to pardon and forgiveness and a good end. I was interested in this manuscript by Mirghani, Hadith and all accounts in reference to the virtues of the great lady to examine a manuscript

Soil is considered one of the main factors of subsidence phenomena which
became continually happen in Baghdad (Ghazalia, Ameria, and Hay al-Amyl)
causing bad effects as shortage of drinking water, traffic jam and formation
swamps.
This thesis depends on soil study to a depth 15 meters, due to its
importance in subsidence. This done through specifying its chemical physical
properties.
Soil within Iraq climate, in case of water stopping for any reason it contract
and shrink away especially when it exposed to high pressure these factors
finally caused subsidence. In case of leakage underground water or that of
damaged water pipes this will contribute to chemical reactions which damage soil
structure and incr

As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .

   The technology of reducing dimensions and choosing variables are very important topics in statistical analysis to multivariate. When two or more of the predictor variables are linked in the complete or incomplete regression relationships, a problem of multicollinearity are occurred which consist of the breach of one basic assumptions of the ordinary least squares method with incorrect estimates results.

 There are several methods proposed to address this problem, including the partial least squares (PLS), used to reduce dimensional regression analysis. By using linear transformations that convert a set of variables associated with a high link to a set of new independent variables and unr

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

In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then  these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.

The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the

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

            In this paper the research represents an attempt of expansion in using the parametric and non-parametric estimators to estimate the median effective dose ( ED50 ) in the quintal bioassay and comparing between  these methods . We have Chosen three estimators for Comparison. The first estimator is
( Spearman-Karber )  and the second estimator is ( Moving Average ) and The Third estimator  is ( Extreme Effective Dose ) . We used a minimize Chi-square as a parametric method. We made a Comparison for these estimators by calculating the mean square error of (ED50) for each one of them and comparing it with the optimal the mean square

In this paper we suggest new method to estimate the missing data  in bivariate normal distribution and compare it with Single Imputation  method (Unconditional mean and Conditional mean) by using simulation.