The question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.

In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes

   In this paper , two method which deal with finding the optimal value for adaptive smoothing constant, are compared .This constant is used in adaptive Single Exponential Smoothing (ASES).

The comparing is between a method uses time domain and another uses frequency domain when the data contain outlier value for autoregressive model of order one AR(1) , or Markov Model, when the time series are stationary and non stationary with deferent samples .    

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 research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .

ملخـــص البحــــث

    من أهم مسائل الطلاق التي كثر حولها الخلاف: (الحلف بالطلاق وتعليقه بشرط )، لذا عمدت في هذه الصفحات اليسيرة ان اتناول بالبحث والدّراسة مسألة تُعَدُّ من المعضلات، وهي (ما يترتّب على الحلف بالطَّلاق إذا حنث الحالف). وقد فشا وكَثُرَ في الأزمنة المتأخرة الحلف بالطَّلاق في المجتمعات المسلمة، مما دفعني للكتابة فيه ببحث وسميته :

(    أحـكام الحلف با

This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

استهدفت الدراسة الحالية تأثير المستخلص الححوني الانيني نحن من فسورنمار نبات التفاح الأخضر Pyrus malus المحلي في نمو ثلاث عزلات من البكتريا عزلتان من البكتريا السالبة لملون غرام (Proteus vulgaris Escherichia (coli) وعزلة من البكتريا الموجبة لملون غرام (Staphyllococcus aureus). اظهرت نتائج الفعالية التثبيطية لمستخلصي القشور واللب الكحولي بطريقة الاقراص تفاوتاً في تأثيرهما تجاه البكتريا المشمولة بالدراسة اذ كان مستخلص القشور الكحولى

Abstract:

The models of time series often suffer from the problem of the existence of outliers ​​that accompany the data collection process for many reasons, their existence may have a significant impact on the estimation of the parameters of the studied model. Access to highly efficient estimators  is one of the most important stages of statistical analysis, And it is therefore important to choose the appropriate methods to obtain good  estimators. The aim of this research is to compare the ordinary estimators and the robust estimators of the estimation of the parameters of

    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.