Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

In this paper  has been one study of autoregressive generalized conditional heteroscedasticity models existence of the seasonal component, for the purpose applied to the daily financial data at high frequency is characterized by Heteroscedasticity seasonal conditional, it has been depending on Multiplicative seasonal Generalized Autoregressive Conditional Heteroscedastic Models Which is symbolized by the Acronym (SGARCH) , which has proven effective expression of seasonal phenomenon as opposed to the usual GARCH models. The summarizing of the research work studying the daily data for the price of the dinar exchange rate against the dollar, has been used autocorrelation function to detect seasonal first, then was diagnosed wi

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

In this research weights, which are used, are estimated using General Least Square Estimation to estimate simple linear regression parameters when the depended variable, which is used, consists of two classes attributes variable (for Heteroscedastic problem) depending on Sequential Bayesian Approach instead of the Classical approach used before, Bayes approach provides the mechanism of tackling observations one by one in a sequential way, i .e each new observation will add a new piece of information for estimating the parameter of probability estimation of certain phenomenon of Bernoulli trials who research the depended variable in simple regression  linear equation. in addition to the information deduced from the past exper

In this paper, the fuzzy logic and the trapezoidal fuzzy intuitionistic number were presented, as well as some properties of the trapezoidal fuzzy intuitionistic number and semi- parametric logistic regression model when using the trapezoidal fuzzy intuitionistic number. The output variable represents the dependent variable sometimes cannot be determined in only two cases (response, non-response)or (success, failure) and more than two responses, especially in medical studies; therefore so, use a semi parametric logistic regression model with the output variable (dependent variable) representing a trapezoidal fuzzy intuitionistic number.

the model was estimated on simulati

The efficiency of attapulgite liners as anti-seepage for crude oil is examined. Consideration is given to the potential use of raw attapulgite and mixture attapulgite with prairie hay and coconut husk as liners to prevent crude oil seepage. Attapulgite clay used in this study was brought from Injana formation /Western Desert of Iraq. Two types of Crude oil brought from Iraqi oil fields were used in experiments; heavy crude oil from East-Baghdad oil field and light crude oil from Nassiriya oil field. Initially the basic properties of attapulgite and crude oils were determined. The attapulgite clay was subjected to mineralogical, chemical and scanning electron microscope analyses. Raw Attapulgite 150µm, 75µm, and 53µm were tested

الحمد لله رب العالمين والصلاة والسلام على نبينا محمد( صلى الله عليه وعلى اله وسلم) وعلى اله وصحبه أجمعين وعلى من سار على نهجه واتبع سننه إلى يوم الدين. يعتمد علماء الحديث والباحثون في العلوم الإسلامية وبعض الدراسات في العلوم الأخرى الأحاديث النبوية الشريفة في دراساتهم وأبحاثهم العلمية، ولذلك يلجأ ون إلى كتب التخريجات التي تهديهم إلى مواضع الأحاديث في مصادرها الأصلية . وزاد التأليف في كتب تخريج الأحاديث لأهمي

يهدف البحث الى استخدام بحوث العمليات في اتخاذ القرارات الادارية لما لها من اهمية في مواكبة التطورات الحاصلة في مجال استراتيجيات الاعمال ونظم المعلوماتية وإدارة المعرفة في القرن الحالي، إذ لم تعد الأساليب التقليدية في اتخاذ القرارات الإدارية مجدية بعد ظهور توجهات حديثة في الإدارة تركز على ضرورة الاعتماد على الأساليب الكمية كبحوث العمليات, وقد تطور استخدام بحوث العمليات في السنوات الماضية بشكل كبير وأصبحت أ