In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

The present study devoted to determine the ultimate lateral carrying capacity of piles foundation in contaminated clayey soils and subjected to lateral cyclical loading. Two methods have been used to calculate the lateral carrying capacity of piles foundation; the first one is two-line slopes intersection method (TLSI) and the second method is a modified model of soil degradation. The model proposed by Heerama and then developed by Smith has been modified to take into consideration the effects of heavy loads and soil contamination. The ultimate lateral carrying capacity of single pile and piles group (2×2) driven into samples of contaminated clayey soils have been calculated by using the two methods. Clayey soil samples are contami

The influence of the reaction gas composition during the DC magnetron sputtering process on the structural, chemical and optical properties of Ce-oxide thin films was investigated. X-ray diffraction (XRD) studies confirmed that all thin films exhibited a polycrystalline character with cubic fluorite structure for cerium dioxide. X-ray photoelectron spectroscopy (XPS) analyses revealed that cerium is present in two oxidation states, namely as CeO2 and Ce2O3, at the surface of the films prepared at oxygen/argon flow ratios between 0% and 7%, whereas the films are completely oxidized into CeO2 as the aforementioned ratio increases beyond 14%. Various optical parameters for the thin films (including an optical band gap in the range of 2.25–3.

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da

  Weibull distribution is considered as one of the most widely  distribution applied in real life, Its similar to normal distribution in the way of applications, it's also considered as one of the distributions that can applied in many fields such as industrial engineering to represent replaced and manufacturing time ,weather forecasting, and other scientific uses in reliability studies and survival function in medical and communication engineering fields.

   In this paper, The scale parameter has been estimated for weibull distribution using Bayesian method based on Jeffery prior information as a first method , then enhanced by improving Jeffery prior information and then used as a se