In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi

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 banking sector is currently facing great challenges resulting from intense competition in the financial environment, and this is what makes the supreme audit bodies and the Central Bank audit as the highest supervisory authority on banks in order to achieve profit and not be exposed to loss, and this requires identifying the banking strengths and risks that constitute points Weakness that affects the future performance and the life of the bank, which requires special supervisory care, and from this point of view, the research aims to use the CAMELS model as a control tool in banks, through the use of its six indicators: capital adequacy, asset quality, management quality, profits, liquidity And sensitivity to market risks, th

The current research aims to identify the effect of the Bransford and Stein model on the achievement of fifth-grade literary students for geography and their reflective thinking. To achieve the objective of the research, the following two null hypotheses were formulated:

• There is no statistically significant difference at the significance level (0.05) between the average scores of the experimental group students who studied geography using the Bransford and Stein model and the average scores of the control group students who studied the same subject in the usual way in the achievement test. 2- There is no statistically significant difference at the significance level (0.05) between the average scores of the experimental gr