As we know the transportation studies regarded as one of a very
important and difficult studies and one of its difficulties created from the
process of data updating therefore the researcher well facing many difficulties
to balancing between the old data on collecting new data.
The research present an opinion which is summarized by: can we use
the old data after we updated and used it as alternatives? Or the researcher
must collect new data to complete their research which indicate to the present
situation and some times they cant complete their studies because of the
security, economic, temporally difficulties.
The research used two kinds of data, the old data which belong to the
period (1998) and new data

In this research is estimated the function of reliability dynamic of multi state systems  and their compounds and for three types of systems (serial, parallel, 2-out-of-3) and about two states (Failure and repair) depending on calculating the structur function allow to describing the behavior of

In this paper, some estimators of the unknown shape parameter and reliability function  of Basic Gompertz distribution (BGD) have been obtained, such as MLE, UMVUE, and MINMSE, in addition to estimating Bayesian estimators under Scale invariant squared error loss function assuming informative prior represented by Gamma distribution and non-informative prior by using Jefferys prior. Using Monte Carlo simulation method, these estimators of the shape parameter and R(t), have been compared based on mean squared errors and integrated mean squared, respectively

The analysis of time series considers one of the mathematical and statistical methods in explanation of the nature phenomena and its manner in a specific time period.

Because the studying of time series can get by building, analysis the models and then forecasting gives the priority for the practicing in different fields, therefore the identification and selection of the model is of great importance in spite of its difficulties.

The selection of a standard methods has the ability for estimation the errors in the estimated the parameters for the model, and there will be a balance between the suitability and the simplicity of the model.

In the analysis of d

Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust  M method after their development through the use of sequential  approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

The multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers  , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg

يعتبر الخزين من الامور الهامة في العديد من الشركات حيث يمثل نسبة 50 % من رأس مال المستثمر الكلي مع شدة الضغط المتمثل الى خفض التكاليف الكلية المتمثلة مع انواع اخرى من حالات عدم التأكد (الضبابية) لذا سوف نقدم في هذا البحث نظام اقتصادي للكميات الكلية ( الانتاج الاقتصادي للكميات) للوصول حجم الدفعة المثلى المضببة (FEOQ) عندما تكون كل المعالم في حالة عدم التأكد حيث يتم تحويلها الى فترة واحدة وبعد ذلك الحصول على حجم الد

        تظهر الحاجة إلى الاستثمارات الرأسمالية من عدة مصادر كالحاجة إلى توسيع المنشآت الإنتاجية ، أو استجابة لحاجات المجتمع كشراء مكائن ومعدات لتخفيض تلوث الماء والهواء. أما أهم مصادر الحاجة لرؤوس الأموال فإنها تأتي من الموجودات الإنتاجية (باستثناء الأرض) ، حيث تستهلك هذه الموجودات (المكائن والآلات والعُدد) بشكل مستمر جراء الاستخدام ، فالمكائن، مثلا ، تسير دائما في طريقها نحو أكوام الخردة وال

  Survival analysis is the analysis of data that are in the form of times from the origin of time until the occurrence of the end event, and in medical research, the origin of time is the date of registration of the individual or the patient in a study such as clinical trials to compare two types of medicine or more if the endpoint It is the death of the patient or the disappearance of the individual. The data resulting from this process is called survival times. But if the end is not death, the resulting data is called time data until the event. That is, survival analysis is one of the statistical steps and procedures for analyzing data when the adopted variable is time to event and time. It could be d