المستويات الدالة للمؤشرة في الفلم التسجيلي العراقي

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

This paper deal with the estimation of the shape parameter (a) of Generalized Exponential (GE) distribution when the scale parameter (l) is known via preliminary test single stage shrinkage estimator (SSSE) when a prior knowledge (a₀) a vailable about the shape parameter as initial value due past experiences as well as suitable region (R) for testing this prior knowledge.

The Expression for the Bias, Mean squared error [MSE] and Relative Efficiency [R.Eff(×)] for the proposed estimator are derived. Numerical results about beha

A preliminary test single stage Shrinkage (PTSSS) techniques is used for estimation the scale parameter q of an exponential distribution when a prior knowledge about q is a available in the form of initial estimate q₀ of q. It is proposed to estimate q by a testimator  that is based upon the result of a test of the hypothesis H₀ :q = q₀ against the hypothesis H_A

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 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 evaluation process of transportation problem required finding basic feasible solution (bfs). Represent the base of decision making process. To purpose start anther batter solution to able from decisions taking process, consider the decision making process, find (bfs) represent the standard form in linear programming (LP). Most important stage of update (bsf) stages that achieved minimum cost (the optimal solution). the goal of paper to improving & evaluation (bfs) by new procedure (proposed method) comparison with Vogel method.

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

سنقوم في هذا البحث باشتقاق توزيع الطلب خلال فترة الانتظار لنظام سيطرة على الخزين يخضع فيه الطلب لتوزيع گاما فيما يخضع وقت الانتظار للتوزيع اللوغايتمي الطبيعي، كما سيتم استخراج العزوم الأساسية لهذا المتغير ، الضرورية بدورها لاستخراج بعض مؤشرات النظام المذكور.

المصطلحات المستخدمة: التكامل المحيط، المستوي المركب، تكامل هانكيل، مستوى إعادة الطلب، الوقاية.