In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

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

Five membered heterocyclics derivatives were synthesized in this work by three routes. The first route includes the synthesis of N-benzoic acid 1,2,3,-triazole derivatives (3),(4) by diazotation of methyl-2-amino benzoate and treating the resulted salt (1) with sodium azide and ethyl acetoacetate or acetyl acetone, respectively. In the second route, derivatives of pyrazole (8) pyrazolin-5-one (9), (10) were prepared by the reaction of the salt (1) with some active methylene compounds to give the corresponding hydrazones derivatives (5-7) which then they were treated with hydrazine hydrate. The third route afforded the synthesis of three derivatives (12), (15a), (15b) of thiazolidinone by two different methods. AII compounds were confirmed b

Condensation of 1,2- dibromo ethane with para hydroxy benzoic acid gave 1,2-Ethane-bis- 4-oxybenzoic [1]. This Compound was converted with the thionyl chloride to give 1,2-Ethane-bis- 4-oxybenzoyl chloride [2]. Reaction of compound [2] with thiosemicarbizades gave 1,2-Ethanebis[4-oxybenzoyl-thiosemicarbazide] [3] and opteined 1,2-Ethane-bis[3-mercapto-5-phenoxy- 1,2,4-triazole] [4] from treatment compound [3] with NaOH (4%) .The new compounds 1,2- Ethane-bis[3-(substituted thioacyl)-4-(substituted acyl)-5 phenoxy-1,2,4-triazole] [5a-d] and 1,2- Ethane-bis[3-(substituted alkylthio)-5 phenoxy-1,2,4-trizole] [5e-f] derived from compound [4] were synthesized and characterized by physical and spectral data. All the compounds [4], [5a-d] and [5e-

 In this work, the preparation of some new oxazolidine and thiazolidine derivatives has been conducted. This was done over two steps; the first step included the synthesis of Schiff bases A1-A5 in 72-88% yields by the condensation of isonicotinic acid hydrazide and aldehydes. The second step includes the cyclization of derivatives A1-A5 with glycolic acid and thioglycolic acid to obtain the desired products, oxazolidine derivatives B1-B5 (44-60% yields) and thiazolidine derivatives C1-C5 (41-61% yields), respectively. The structure of the prepared compounds was characterized using FT-IR, 1H NMR, and 13C NMR spectroscopy. Some of the produced compounds were tested for antioxidant properties.  

 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 others

 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

This work includes synthesis of new six membered heterocyclic rings with effective amino group using the reaction of benzylideneacetophenone (chalcone) (1) with thiourea or urea in alcoholic basic medium to form: 1,3-thiazen-2-amine (2), and 1,3-oxazin-2-amine (8) respectively. The diazotization reaction was carried out with sodium nitrite in presence of hydrochloric acid to form diazonium salts which suffered coupling reaction with naphthols and phenols in the presence of sodium hydroxide to form colored azo dyes (4-7, and 10-13). o-methylation reaction of compounds (7) and (10) yielded : 1,3-thiazin -2-yl-diazenyl (14), and 1,3-oxazin-2-yl-diazenyl (15) respectively.The new compounds were characterized using vario