In this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.

     The study of improved model for measuring the total nuclear fusion cross section characteristics  the D-D reaction may play an important role in deciding  or determining the hot plasma parameters such as mean free path , the reaction rate , reactivity and energy for emitted neutrons or protons in our work we see the it is necessary to modify the empirical formulas included the total cross section in order to arrive or achieve good agreement with the international publish result.    

The effect of short range correlations on the inelastic longitudinal Coulomb form
factors for the lowest four excited 2+ states in 18O is analyzed. This effect (which
depends on the correlation parameter β) is inserted into the ground state charge
density distribution through the Jastrow type correlation function. The single particle
harmonic oscillator wave function is used with an oscillator size parameter b. The
parameters β and b are, considered as free parameters, adjusted for each excited state
separately so as to reproduce the experimental root mean square charge radius of
18O. The model space of 18O does not contribute to the transition charge density. As
a result, the inelastic Coulomb form factor of 18

This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.

Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colo

Background: Osteoporosis is an extra-articular complication of rheumatoid arthritis that results in increased risk of fractures and associated morbidity, mortality, and healthcare costs. Objective: To evaluate changes in bone mineral density in a sample of rheumatoid arthritis (RA) patients on biological (anti tumor necrosis factor (TNF) alpha) and non-biological agent disease modifying antirheumatic drugs (DMARDs). Patients and Methods: A cross sectional study enrolled 60 RA patients diagnosed by rheumatologist according to the 2010 American College of Rheumatology/European League Against Rheumatism (2010 ACR/EULAR) classification criteria for RA. Thirty patient on biological agent (anti TNF alpha) and 30 patient on non-biological agent (D