The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the analysis of income inequality and wealth distribution using the Dagum model.
In this study, we investigate about the estimation improvement for Autoregressive model of the third order, by using Levinson-Durbin Recurrence (LDR) and Weighted Least Squares Error ( WLSE ).By generating time series from AR(3) model when the error term for AR(3) is normally and Non normally distributed and when the error term has ARCH(q) model with order q=1,2.We used different samples sizes and the results are obtained by using simulation. In general, we concluded that the estimation improvement for Autoregressive model for both estimation methods (LDR&WLSE), would be by increasing sample size, for all distributions which are considered for the error term , except the lognormal distribution. Also we see that the estimation improve
... Show MoreThe purpose of the study is to investigate the effect of the constructivist model of yager in acquiring the geographical concepts among first intermediate students in geography. The study was carried on based on the null hypothesis, which states, there is no significant difference at the level of (0.05) between the experimental group that follows yager model in learning the principles of geography, and the control group that studies the same subject considering the traditional methods of learning, the. To do so, a sample of (70) first-intermediate student were chosen purposefully from two random class for the academic year (2016-2017) divided into two groups. The selected schools located at Al-rusafa side in the city of Baghdad, as well
... Show MoreThe European Unit has never been affected by a serious phenomena as the phenomena of the advancing of the far right parties. Though these parties vary in their impact in their original countries, they agree on one important issue which is the deconstruction of the European unit and limiting its supernational powers. These increasing popular parties aim at more national independence in decision making away from the decisions taken by Brussels. Moreover, they criticize the financial and administrative corruption accompanied many of the rescuing procedures directed for example towards countries like Greece and Spain during the international economic crisis. This failure nourishes many of the negative feelings against the European unit which
... Show MoreNegotiations are distinguished in that they are an easy and simple means between the conflicting parties, and it is an effective means at the same time as the conflicting parties seek understanding on the most effective way to solve their dispute, but negotiations are not always appropriate to resolve international disputes, especially when there is a disparity in power between the negotiating countries, or when it is missing Goodwill, or even when one of the parties is absent or less flexible, and the internal circumstances of one of the conflicting countries may play a negative or positive role in the success of the negotiations, away from the influence of the role of external variables in that, a
... Show MoreThe neutron, proton, and matter densities of the ground state of the proton-rich 23Al and 27P exotic nuclei were analyzed using the binary cluster model (BCM). Two density parameterizations were used in BCM calculations namely; Gaussian (GS) and harmonic oscillator (HO) parameterizations. According to the calculated results, it found that the BCM gives a good description of the nuclear structure for above proton-rich exotic nuclei. The elastic form factors of the unstable 23Al and 27P exotic nuclei and those of their stable isotopes 27Al and 31P are studied by the plane-wave Born approximation. The main difference between the elastic form factors of unstable nuclei and the
... Show MoreThe process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material
... Show MoreThe evolution of cryptography has been crucial to preservation subtle information in the digital age. From early cipher algorithms implemented in earliest societies to recent cryptography methods, cryptography has developed alongside developments in computing field. The growing in cyber threats and the increase of comprehensive digital communications have highlighted the significance of selecting effective and robust cryptographic techniques. This article reviews various cryptography algorithms, containing symmetric key and asymmetric key cryptography, via evaluating them according to security asset, complexity, and execution speed. The main outcomes demonstrate the growing trust on elliptic curve cryptography outstanding its capabi
... Show MoreThe COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
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