Abstract:                                        

   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelate

Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

The aim of this research is to estimate the area unit function of productivity for the potato crop in Anbar province for the autumn season (2008 / 2009) Anbar province has been chosen as an applied model for the study due to its well known in cultivating potato crop , and the data were collected through a random sample about (10%) from the study society with a (150) farmers,  The results indicated that the double logarithmic formula was the best representative of the relationship between crop productivity and independent variables (quantity of potato tubers , quantity of herbicides stuffs, quantity of fertilizer , hours of mechanical labour

يھدف البحث الى اجراء تقدير دالة المعولية لتوزيــع ويبل ذي المعلمتين بالطرائـق المعلميــة والمتمثلة بـ (NWLSM,RRXM,RRYM,MOM,MLM (، وكذلك اجراء تقدير لدالة المعولية بالطرائق الالمعلمية والمتمثلة بـ . (EM, PLEM, EKMEM, WEKM, MKMM, WMR, MMO, MMT) وتم استخدام اسلوب المحاكاة لغرض المقارنة باستخدام حجوم عينات مختلفة (20,40,60,80,100) والوصول الى افضل الطرائق في التقدير باالعتماد على المؤشر االحصائي متوسط مربعات الخطا التكاملي (IMSE(، وقد توصل البحث الى

Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use

The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.