Abstract

       The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a he

  Many managers in geometrical and technical organizations prefer to deal with quantitative values ​​to choose between the available options and choose the best alternative to avoid randomization and bias in decision making. One of them Baghdad Water Department, which seeks to develop the quality of its product (drinking water) and achieve its objectives under increasing growing population and the demand for water, Some of TQM tools, especially the statistical, have this ability because there is chance to use historical data and experiment of employees in Application . Two statistical tools were applied: the nominal group technique, matrix data analysis technique as well as the brainstorming tool to search for the best o

Abstract 

The Phenomenon of Extremism of Values ​​(Maximum or Rare Value) an important phenomenon is the use of two techniques of sampling techniques to deal with this Extremism: the technique of the peak sample and the maximum annual sampling technique (AM) (Extreme values, Gumbel) for sample (AM) and (general Pareto, exponential) distribution of the POT sample. The cross-entropy algorithm was applied in two of its methods to the first estimate using the statistical order and the second using the statistical order and likelihood ratio. The third method is proposed by the researcher. The MSE comparison coefficient of the estimated parameters and the probability density function for each of the distributions were

The problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline

إن الأبحاث العلمية كانت و لا تزال تحضا باهتمام الكثير من العلماء و المختصين في مجال التربية الرياضية بشكل عام و الجمناستك بشكل خاص لإيجاد أحدث الوسائل و الأدوات التي تساعد على سهولة توصيل المعلومات إلى المتعلمين و بدرجة عالية من الكفاءة, إذ يمكن للمتعلم الاستعانة بوسائل تعليمية عديدة منها القراءات المختلفة و المواد المبرمجة أو الأفلام و الوسائل السمعية و البصرية و ما إلى ذلك, فالمعلم الذي يستخدم هذه الوسائل

:يمتاز مرض قصور الدرقية بإنخفاض مستوى هرمونات T3و T4الضرورية لعمليات إنتاج الطاقة و حيوية الجسم ؛ لذلك ترافق هذه الحالة إضطرابات في عمليات الأيض المختلفة في الجسم . أجريت الدراسة في المركز التخصصي للغدد الصم و السكري في بغداد ، و شملت 70ًاضيرممن مرضى قصور الدرقية ، تم تشخيص الحالة لديهم عن طريق قياس مستويات الهرمونات (TSH,T4,T3). كما شملت 60اوريتخأًاصخشبشكل عشوائي من غير مرضى الغدة ، و قد تم التأكد من سلامة الغدة وعدم

In this paper, we present a comparison of double informative priors which are assumed for the parameter of inverted exponential distribution.To estimate the parameter of inverted exponential 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 inverted exponential distribution. Also assumed Chi-squared - Gamma distribution, Chi-squared - Erlang distribution, and- Gamma- Erlang distribution as double priors. The results are the derivations of these estimators under the squared error loss function with three different double priors.

Additionally Maximum likelihood estimation method

Maulticollinearity is a problem that always occurs when two or more predictor variables are correlated with each other. consist of the breach of one basic assumptions of the ordinary least squares method with biased estimates results, There are several methods which are proposed to handle this problem including the  method To address a problem  and  method To address a problem , In this research a comparisons are employed between the biased   method and unbiased   method with Bayesian   using Gamma distribution  method  addition to Ordinary Least Square metho

The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.