In linear regression, an outlier is an observation with large residual.  In other words, it is an observation whose dependent-variable value is unusual given its values on the predictor variables. An outlier observation may indicate a data entry error or other problem.

An observation with an extreme value on a predictor variable is a point with high leverage. Leverage is a measure of how far an independent variable deviates from its mean. These leverage points can have an effect on the estimate of regression coefficients.

Robust estimation for regression parameters deals with cases that have very high leverage, and cases that are outliers. Robust estimation is essentially a

The main aim of this paper is to study how the different estimators of the two unknown parameters (shape and scale parameter) of a generalized exponential distribution behave for different sample sizes and for different parameter values. In particular, 

. Maximum Likelihood, Percentile and Ordinary Least Square estimators had been implemented for different sample sizes (small, medium, and large) and assumed several contrasts initial values for the two parameters. Two indicators of performance Mean Square Error and Mean Percentile Error were used and the comparisons were carried out between different methods of estimation  by using monte carlo simulation techniq

In this paper we suggest new method to estimate the missing data  in bivariate normal distribution and compare it with Single Imputation  method (Unconditional mean and Conditional mean) by using simulation. 

This research deals with parameters estimation methods for the intensity function of non homogeneous poisson processes , it aims to estimate parameters of this function throughout three methods which are maximum likelihood method , moment method and shurnkage method using simulation method.

In order to achive the best method, several assumed values for parameters of intensity function have been adopted  using sample size of 
(14, 25, 50, 100) .Results of estimation showed that the estimation over the estimation method , of maximum likelihood and moment .

  This estimation gain the least mean of squares error for the above samples .

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In this research weights, which are used, are estimated using General Least Square Estimation to estimate simple linear regression parameters when the depended variable, which is used, consists of two classes attributes variable (for Heteroscedastic problem) depending on Sequential Bayesian Approach instead of the Classical approach used before, Bayes approach provides the mechanism of tackling observations one by one in a sequential way, i .e each new observation will add a new piece of information for estimating the parameter of probability estimation of certain phenomenon of Bernoulli trials who research the depended variable in simple regression  linear equation. in addition to the information deduced from the past exper

The development in manufacturing computers from both (Hardware and Software) sides, make complicated robust estimators became computable and gave us new way of dealing with the data, when classical discriminant methods failed in achieving its optimal properties especially when data contains a percentage of outliers. Thus, the inability to have the minimum probability of misclassification. The research aim to compare robust estimators which are resistant to outlier influence like robust H estimator, robust S estimator and robust MCD estimator, also robustify misclassification probability with showing outlier influence on the percentage of misclassification when using classical methods. ,the other

Reliability has an important role in both the industrial and engineering applications. So the need for Reliability Tests appeared are series of tests a discover out of factors that  appear through the test, knowledge limit of fit a specifics production addition for getting on goodness of production.

Therefore, the need for research to test for censor data from ( Type II ) for exponential distribution with one parameter and that test it’s (Reliability Growth) includes three curves are Idealized Growth curve estimation parameters and reliability with maximum likelihood method, Duane Growth curve takes estimation parameters and reliability with least squares method, Exponential Reliability Growth Cur

تقدير النموذج اللوجستي باستخدام اوزان بيز المتسلسل

One of the most important problems in the statistical inference is estimating parameters and Reliability parameter and also interval estimation , and testing hypothesis . estimating two parameters of exponential distribution and also reliability parameter in a stress-strength model.

This parameter deals with estimating the scale parameter and the Location parameter µ , of two exponential distribution   ,using moments estimator and maximum likelihood estimator , also we estimate the parameter R=pr(x>y), where x,y are two- parameter independent exponential random variables .

Statistical properties of this distribution and its properti

 يدرس هذا البحث طرائق اختزال الابعاد التي تعمل على تجاوز مشكلة البعدية عندما تفشل الطرائق التقليدية في ايجاد تقدير جيد للمعلمات، لذلك يتوجب التعامل مع هذه المشكلة بشكل مباشر. ومن اجل ذلك، يجب التخلص من هذه المشكلة لذا تم استعمال اسلوبين لحل مشكلة البيانات ذات الابعاد العالية الاسلوب الاول طريقة الانحدار الشرائحي المعكوس SIR ) ) والتي تعتبر طريقة غير كلاسيكية  وكذلك طريقة ( WSIR ) المقترحة والاسلوب الثاني طري