في هذا البحث سيتم دراسة أنموذج الانحدار اللامعلمي الذي يعاني فيه متغير الأستجابة من حالة فقدان (عدم استجابة) في بعض مشاهداتة وتحت أفتراض الية فقدان MCAR، إذ تم اقتراح طريقة تعويض قاعدة Kernel الأحادي اللامعلمي بدلاً عن القيمة المفقودة ومقارنة هذه الطريقة مع طريقة تعويض أقرب مجاور بأستخدام أسلوب المحاكاة والمتمثل بعدة تجارب لعدة نماذج مختلفة ولحالات مختلفة من حجوم العينة، التباين ونسب الفقدان.             <

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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        يقدم هذا البحث الانموذج الرمادي GM(1,1) من الرتبة الأولى و بمتغير واحد و هو أساس نظرية النظام الرمادي تناول هذا البحث خصائص الانموذج الرمادي ومجموعة من طرائق تقدير معالم الانموذج الرمادي GM(1,1) وهي طريقة المربعات الصغرى (LS) , طريقة المربعات الصغرى الموزونة (WLS) , طريقة المربعات الصغرى الكلية (TLS) و طريقة الانحدار التدريجي (DS) حيث تمت المقارنة بين هذه الطرق اعتمادا على نوعين من المقاييس متوسط مربع الخطأ MSE))

ان الهدف من الدراسة هو بيان القدرة التنبؤية الافضل بين انموذج الانحدار اللوجستي والدالة المميزة الخطية باستعمال البيانات الاصليه اولا ثم المركبات الرئيسة لتقليص الابعاد بين المتغيرات لبيانات المسح الاجتماعي والاقتصادي للاسرة لمحافظة بغداد لعام 2012 وتضمنت عينة البحث 615 مفردة لـ13 متغير، 12منها متغير توضيحي والمتغير المعتمد شمل العاملين والعاطلين عن العمل، تم اجراء المقارنة بين الطريقتين اعلاه واتضح من خلال

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. 

The estimation of the parameters of Two Parameters Gamma Distribution in case of missing data has been made by using two important methods: the Maximum Likelihood Method and the Shrinkage Method. The former one consists of three methods to solve the MLE non-linear equation by which the estimators of the maximum likelihood can be obtained: Newton-Raphson, Thom and Sinha methods. Thom and Sinha methods are developed by the researcher to be suitable in case of missing data. Furthermore, the Bowman, Shenton and Lam Method, which depends on the Three Parameters Gamma Distribution to get the maximum likelihood estimators, has been developed. A comparison has been made between the methods in the experimental aspect to find the best meth

In this paper, the generalized inverted exponential distribution is considered as one of the most important distributions in studying failure times. A shape and scale parameters of the distribution have been estimated after removing the fuzziness that characterizes its data because they are triangular fuzzy numbers. To convert the fuzzy data to crisp data the researcher has used the centroid method. Hence the studied distribution has two parameters which show a difficulty in separating and estimating them directly of the MLE method. The Newton-Raphson method has been used.

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

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

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