The repeated measurement design is called a complete randomized block design for repeated measurement when the subject is given the all different treatments , in this case the subject is considered as a block . Many of nonparametric methods were considered like Friedman test (1937) and Koch test(1969) and Kepner&Robinson test(1988) when the assumption of normal distribution of the data is not satisfied .as well as F test  when the assumptions of the analysis of variance is satisfied ,where the observations within blocks are assumed to be equally correlated . The purpose of this paper is to summarize the result of the simulation study for comparing these methods as well as present the suggested

Me

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

أن استعمال النماذج المعلمية وما يتبعها من أساليب تقدير يتطلب وجود العديد من الشروط الأولية الواجب توافرها كي تمثل تلك النماذج المجتمع تحت الدراسة تمثيلا ملائما الأمر الذي دفع الباحثون إلى البحث عن نماذج أكثر مرونة من النماذج المعلمية وتمثلت هذه النماذج بالنماذج اللامعلمية .     في هذا البحث تم مقارنة ما يسمى بمقدر Nadaraya-Watson في حالة استعمال معلمة عرض حزمة ثابتة ومتغيرة وذلك من خلال أسلوب المحاكاة مستخد

في هذا البحث تم استعمال احد الاساليب التقريبية وهو ما يسمى اسلوب المعدل الموزون للنقاط المقربة (Weighted Average of Rounded Points-WARPing) لتقدير انبعاثات ثاني اوكسيد الكاربون CO_2 في العراق عند استعمال مقدريNadaraya-Watson, Local Linear estimator للفترة الممتدة من عام (1990) ولغاية (2019) ومن ثم المقارنة بين اداء تلك المقدرات وقد اثبتت النتائج تفوق طريقة Local Linear estimator وخاصة في النقاط عند نقاط الحد وتميزها عن طريقة Nadaraya–Watson على الرغم من الاداء ا

Performance measures are a central component of management control system, making good planning and control decisions requires information about how different subunits of organizations have performed. To be effective, performance measures (both financial and nonfinancial) must also motivate managers and employees at all levels of organization to strive to achieve organization goals.

To give aclear picture about performance must be used compound measure, that was best than single measure.

Altman model can be used as a compound performance measure that measures the performance by tied a sum of variables, due to make weight for every variable to reach for performance.

زاد اهتمام الباحثين في السنوات الاخيرة بنماذج الانحدار شبه المعلمية وذلك اذ يمكن من خلالها دمج نماذج الانحدار اللامعلمي والمعلمي في ان واحد ومن ثم تكوين انموذج انحدار يتميز بامكانية التعامل مع مشكلة تعدد الابعاد الموجودة في النماذج اللامعلمية والتي تحصل عند زيادة عدد المتغيرات التوضيحية الداخلة في التحليل و من ثم تناقص دقة التقدير.  فضلا عن امتياز هذا النوع من النماذج بمرونة في المجال التطبيقي مقارنةً

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

In this research, one of the nonlinear regression models is studied, which is BoxBOD, which is characterized by nonlinear parameters, as the difficulty of this model lies in estimating its parameters for being nonlinear, as its parameters were estimated by some traditional methods, namely the method of non-linear least squares and the greatest possible method and one of the methods of artificial intelligence, it is a genetic algorithm, as this algorithm was based on two types of functions, one of which is the function of the sum of squares of error and the second is the function of possibility. For comparison between the methods used in the research, the comparison scale was based on the average error squares, and for the purpose of data ge

المستخلص ان عملية تقدير الانموذج وأختيار المتغير المعنوي هي عملية حاسمة في النمذجة شبه المعلميه semi-parametric modeling)) ففي بدايه عملية النمذجة كثيرا" ما يكون هنالك عدد كبير من المتغيرات التوضيحية لتجنب فقدان أي عناصر تفسيريه قد تكون هامة ونتيجة لذلك فأن أختيار المتغيرات المعنوية أصبحت ضرورة فضلاً عن ان عملية أختيار المتغير ليس الغرض منه تبسيط الأنموذج المعقد وتفسيره فقط ولكن كذلك القدرة على التنبؤ . في هذا ا

         The availability of statistical data plays an important role in planning process. The importance of this research which deals with safety of statistical data from errors and outliers values. The Objective of this study is to determine the outlier values in statistical data by using modern exploratory data methods and comparing them with parametric methods. The research has been divided into four chapters ,the main important conclusions reached are:1-The exploratory methods and the parametric methods showed variation between them in determining the outlier values in the data.

2-The study showed that the box plot method was the best method used in determining