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.
This study was conducted in College of Science \ Computer Science Department \ University of Baghdad to compare between automatic sorting and manual sorting, which is more efficient and accurate, as well as the use of artificial intelligence in automated sorting, which included artificial neural network, image processing, study of external characteristics, defects and impurities and physical characteristics; grading and sorting speed, and fruits weigh. the results shown value of impurities and defects. the highest value of the regression is 0.40 and the error-approximation algorithm has recorded the value 06-1 and weight fruits fruit recorded the highest value and was 138.20 g, Gradin
Journal of Theoretical and Applied Information Technology is a peer-reviewed electronic research papers & review papers journal with aim of promoting and publishing original high quality research dealing with theoretical and scientific aspects in all disciplines of IT (Informaiton Technology
In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de
... Show MoreA pseudo-slug flow is a type of intermittent flow characterized by short, frothy, chaotic slugs that have a structure velocity lower than the mixture velocity and are not fully formed. It is essential to accurately estimate the transition from conventional slug (SL) flow to pseudo-slug (PSL) flow, and from SL to churn (CH), by precisely predicting the pressure losses. Recent research has showed that PSL and CH flows comprise a significant portion of the conventional flow pattern maps. This is particularly true in wellbores and pipelines with highly deviated large-diameter gas-condensate wellbores and pipelines. Several theoretical and experimental works studied the behavior of PSL and CH flows; however, few models have been suggested to pre
... Show MoreThis study is about the role of the Internet in spreading rumors, especially through social networking sites "Facebook" model as the effectiveness of social networks lies in the speed of transmission of events; these two characteristics are important to the public, making the Internet a strong contender for television and its relationship with the public. That's why we find that the Internet today has become a fertile environment for the growth and spread of rumors. The more limited the platforms and places of publication, the greater the responsibility in the search for the original source in spreading this or that rumor, as the Internet is considered an easy means in the production, spreading and re-spreading of
... Show MoreThe study seeks to investigate the effect of Dunn Dunn learning style model on students’ achievement. Besides, the way of developing students’ deductive thinking by testing the null hypothesis: there is no significant difference between experimental group who takes Dunn Dunn model as style in studying geography and control group that follows a traditional method in studying geography at the level of (0,05). Additionally, there is no significant difference between experimental group who takes Dunn Dunn model as style in studying geography and control group that follows a traditional method in studying geography at the level of (0,05) on testing developing deductive thinking skills. The researcher adopted a quasi-experimental posttest
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