The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I distribution by using Bayes estimation, will be  used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of Pareto  type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for

تناول البحث نموذج الانحدار الذاتي الحيزي ونموذج الخطأ الحيزي في محاولة لتقديم دليل عملي يوضح اهمية التحليل الحيزي، مع التركيز بصفة خاصة على أهمية استعمال نماذج الانحدار الحيزي والتي تضم كل منها الاعتمادية الحيزية التي يتم أختبار وجودها من عدمه بأختبار موران، وان تجاهل  هذه الاعتمادية قد يؤدي إلى ضياع معلومات مهمة عن تلك الظاهرة تنعكس في نهاية المطاف على قوة تقدير المؤشر الإحصائي المستخرج، تعدّ هذه الن

تناول البحث نموذج الانحدار الذاتي الحيزي ونموذج الخطأ الحيزي في محاولة لتقديم دليل عملي يوضح اهمية التحليل الحيزي، مع التركيز بصفة خاصة على أهمية استعمال نماذج الانحدار الحيزي والتي تضم كل منها الاعتمادية الحيزية التي يتم أختبار وجودها من عدمه بأختبار موران، وان تجاهل  هذه الاعتمادية قد يؤدي إلى ضياع معلومات مهمة عن تلك الظاهرة تنعكس في نهاية المطاف على قوة تقدير المؤشر الإحصائي المستخرج، تعدّ هذه الن

In this research work an attempt has been made to investigate about the Robustness of the Bayesian Information criterion to estimate the order of the autoregressive process when the error of this model,  Submits to a specific distributions and different cases of the time series on various size of samples by using the simulation,  This criterion has been studied by depending on ten distributions, they are (Normal, log-Normal, continues uniform, Gamma , Exponential, Gamble, Cauchy, Poisson, Binomial, Discrete uniform) distributions, and then it has been reached to many collection and recommendations related to this object , when the series residual variable is subject to each  ( Poisson , Binomial , Exponential , Dis

يعد الهواء من الضروريات لعيش الانسان وكلما كان الهواء نقياً كلما كانت صحة الانسان جيدة، وفي الآونة الاخيرة اصبح الهواء يتأثر بالملوثات وهنالك عدة متغيرات تؤثر في نقاوة الهواء واصبح الهواء يؤثر على صحة الانسان لما يحمله من ملوثات توثر على جسم الانسان وصحته. ولمعرفة مدى تلوث الهواء في كل مناطق الارض تم بناء مؤشر لمعرف تلوث الهواء بالاعتماد على عدة متغيرات يسمى بمعامل تأثير الهواء. ولبيان اكثر المتغيرات تأ

The goal beyond this Research is to review methods that used to estimate Logistic distribution parameters. An exact estimators method which is the Moment method, compared with other approximate estimators obtained essentially from White approach such as: OLS, Ridge, and Adjusted Ridge as a suggested one to be applied with this distribution. The Results of all those methods are based on Simulation experiment, with different models and variety of  sample sizes. The comparison had been made with respect to two criteria: Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE).  

The research aims to estimate missing values using covariance analysis method Coons way to the variable response or dependent variable that represents the main character studied in a type of multi-factor designs experiments called split block-design (SBED) so as to increase the accuracy of the analysis results and the accuracy of statistical tests based on this type of designs. as it was noted in the theoretical aspect to the design of dissident sectors and statistical analysis have to analyze the variation in the experience of experiment )SBED) and the use of covariance way coons analysis according to two methods to estimate the missing value, either in the practical side of it has been implemented field experiment wheat crop in

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 paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the  and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.

Each phenomenon contains several variables. Studying these variables, we find mathematical formula to get the joint distribution and the copula that are a useful and good tool to find the amount of correlation, where the survival function was used to measure the relationship of age with the level of cretonne in the remaining blood of the person. The Spss program was also used to extract the influencing variables from a group of variables using factor analysis and then using the Clayton copula function that is used to find the shared binary distributions using multivariate distributions, where the bivariate distribution was calculated, and then the survival function value was calculated for a sample size (50) drawn from Yarmouk Ho