Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem

Abstract

The traffic jams taking place in the cities of the Republic of Iraq in general and the province of Diwaniyah especially, causes return to the large numbers of the modern vehicles that have been imported in the last ten years and the lack of omission for old vehicles in the province, resulting in the accumulation of a large number of vehicles that exceed the capacity of the city's streets, all these reasons combined led to traffic congestion clear at the time of the beginning of work in the morning, So researchers chose local area network of the main roads of the province of Diwaniyah, which is considered the most important in terms of traffic congestion, it was identified  fuzzy numbers for

بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته

Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.

    To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

Abstract

The Non - Homogeneous Poisson  process is considered  as one of the statistical subjects which had an importance in other sciences and a large application in different areas as waiting raws and rectifiable systems method , computer and communication systems and the theory of reliability and many other, also it used in modeling the phenomenon that occurred by unfixed way over time (all events that changed by time).

This research deals with some of the basic concepts that are related to the Non - Homogeneous Poisson process , This research carried out two models of the Non - Homogeneous Poisson process which are the power law model , and Musa –okumto ,   to estimate th

In this paper, the Monte-Carlo simulation method was used to compare the robust circular S estimator with the circular Least squares method in the case of no outlier data and in the case of the presence of an outlier in the data through two trends, the first is contaminant with high inflection points that represents contaminant in the circular independent variable, and the second the contaminant in the vertical variable that represents the circular dependent variable using three comparison criteria, the median standard error (Median SE), the median of the mean squares of error (Median MSE), and the median of the mean cosines of the circular residuals (Median A(k)). It was concluded that the method of least squares is better than the

Abstract :

    In view of the fact that high blood pressure is one of the serious human diseases that a person can get without having to feel them, which is caused by many reasons therefore it became necessary to do research in this subject and to express these many factors by specific causes through studying it using (factor analysis).

  So the researcher got to the five factors that explains only 71% of the total variation in this phenomenon is the subject of the research, where ((overweight)) and ((alcohol in abundance)) and ((smoking)) and ((lack of exercise)) are the reasons that influential the most in the incidence of this disease.

The aim of this study is to estimate the parameters and reliability function for kumaraswamy distribution of this two positive parameter  (a,b > 0), which is a continuous probability that has many characterstics with the beta distribution with extra advantages.

The shape of the function for this distribution and the most important characterstics are explained and estimated the two parameter (a,b) and the reliability function for this distribution by using the maximum likelihood method (MLE) and Bayes methods. simulation experiments are conducts to explain the behaviour of the estimation methods for different sizes depending on the mean squared error criterion the results show that the Bayes is bet