هناء سعد محمد شبيب

الملخص: اعتمدت هذه الدراسة في تحقيق اهدافها على تحليل السلاسل الزمنية للمدة (2000-2013) وذلك من خلال استخدام الاساليب الاحصائية والقياسية المناسبة ،حيث اظهرت النتائج ان السلاسل الزمنية قيد الدراسة غير مستقرة في مستوياتها ولكنها مستقرة عند اخذ الفروق الاولى لها باستخدام اختبارات جذر الوحدة ،،كما اظهرت نتائج اختبارات التكامل المشترك لـ انجل وكرانجر وجود علاقة توازنية على المدى الطويل بين الناتج المحلي الاجمالي واسعار النفط ،وقد كانت سرعة تعديل اختلال النموذج المقدر تقدر بـ 42.93% سنويا. تحليل البيانات واستخراج النتائج تم من خلال استخدام برنامج .Eviews7.0

Over the past decades, Iraq has witnessed an important population movement, and in many periods, it has been characterized by a high rate and expansion of its repercussions. This movement has included internal migration from rural to urban areas, and from small towns to big cities, it also included significant number of uprooted population inside Iraq, and the dense migration to outside of Iraq. The phenomenon of displacement is one of the most prominent population phenomena witnessed by Iraq in recent decades, which led to the masses of the population of a number of areas to move to other places and regions. The reason of this displacement of high incidence has been violence and armed attacks. The current humanitarian crisis did not happen suddenly. With the fall of Mosul on June 10th, 2014, a series of parallel and interlocking developments caused this large and unexpected event, including the ability of terrorist gangs to control up to one third of Iraqi territory, and the subsequent waves of displacement. In this research, multivariate statistical analysis methods were applied. The Cluster Analysis method was used to identify the disparities in the distribution of IDP camps among the Iraqi governorates after Mosul events in terms of the number of displaced families, and the distribution of families. A multivariate discriminating analysis was also used to identify the type of displacement camps (tents and caravans) that contribute significantly to this displacement variance.

In this article, we used approximate methods to obtain Bayes method estimations for the shape and scale parameters of the generalized exponential distribution, as three approximation methods were employed: Lindley approximation and neutrosophic Lindley approximation, Gibbs sampling and neutrosophic Gibbs sampling, the most important samples based on the gamma informative prior under the squared error loss function. Through different simulation experiments a comparison was made between those estimators of these three approximate methods, from the simulation results we found a relative preference for the important sampling method over the other two methods. The results of simulation experiments were also confirmed by applying these approximate methods to real data representing the operating times of one of the machines of the publishing, printing, and translation house in Baghdad. On the other hand, we apply the same method to the neutrosophic exponential distribution, and the results will be compared to the classical case.

In this article, a set of common statistical models, namely, linear, logarithmic, inverse, quadratic, cube, complex, power, exponential, and logistic model have been fitted to data representing the number of infections with Covid-19 virus in Iraq from the beginning of the disease until now by using the principle of fuzziness by forming a fuzzy information system (FIS) by generating values belonging to the set of infected numbers to produce a classical set that takes into account the inaccuracy (certainty) in data collection, then testing the significance of the models that were appropriate using the F-test and the probabilistic value sigma, and the comparison between these models using the coefficient of determination R2 and MSE to reach the best model that represents the data of infection with the Covid-19 virus. Then estimate the best among those models and to calculate the estimated values for the number of infections with the virus. It was concluded that the use of the principle of fuzziness in the fitting of the models led to an increase in the accuracy of these models and the mean squares error (MSE) for all the models that have been fitted is reduced. We also note that the best model in representing the data of infections with the Covid-19 virus is the Power model, which recorded the lowest MSE among all the models, followed by the Logistic, Compound, Exponential models with the same strength of fit, with the same MSE at all -cut coefficients (0.0, 0.1, 0.5, 0.8) and that the models Cubic, Quadratic, Linear, Logarithmic, Inverse are not suitable for data on the number of infections with Covid-19 virus, and we also note that the best model that achieved a fit for the data was at the -cut = 0.8 (MSE= 0.223) and that the value of the coefficient of the determination R2 of the Power model decreases as the cut-off factor increases and this indicates the accuracy of the appropriate model. We also notice that increase in one unit of time led to increase infection with Covid-19 with 1.456.

In this article, we will used vary formulas of Lindley distribution which are two parameter Lindley distribution under mixture parameter

تعج د ا رسة الججوى الاقترادية الاستثسارية مغ السػاضيع السيسة سػاءً عمى مدتػى الػحجة الاقترادية أو عمى مدتػى الاقتراد القػمي, ك ػف مدتقبل الػحجة الاقترادية أو الاقتراد القػمي ككل يعتسج عمى نجاح السذاريع الاستثسارية, تيجؼ ىحه الج ا رسة لإيجاد بجيل عغ مػلجات الجيديل )الأىمية( لتجييد سكاف قخية الغجيخ بالصاقة الكيخبائية و تعسل بالتشاوب مع التجييد الػششي لمتيار الكيخبائي, و يترف ىحا البجيل ) السشطػمات الذسدية ( بأثخ بيئي جيج عكذ السػلجات الأىمية ذات الأثخ البيئي الدمبي. تع استخجا معاييخ التجارية ) السخرػمة و غيخ السخرػمة ( وكحلظ تحميل الحداسية, حيث كانت الشتائج الشيائية مقبػلة, أي إف السذخوع ذو ججوى اقترادية, لحلظ يشرح السدتثسخيغ بالاستثسار في مجاؿ الصاقػػػػػػػة البجيمػػػة ) الصاقة الذسدية (.