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A multivariate Bayesian model using Gibbs sampler with real data application
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In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collected from the UCI Machine Learning Repository. The findings were discussed and summarized at the end. All calculations for this research have been done using R software (version 4.2.2). © 2024 Author(s).

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 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

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 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

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Publication Date
Wed Mar 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Application of Finite Element Technique: A Review Study
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The finite element approach is used to solve a variety of difficulties, including well bore stability, fluid flow production and injection wells, mechanical issues and others. Geomechanics is a term that includes a number of important aspects in the petroleum industry, such as studying the changes that can be occur in oil reservoirs and geological structures, and providing a picture of oil well stability during drilling. The current review study concerned about the advancements in the application of the finite element method (FEM) in the geomechanical field over a course of century.

Firstly, the study presented the early advancements of this method by development the structural framework of stress, make numerical computer solution

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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Engineering
A Developed Model for Selecting Optimum Locations of Water Harvesting Dams Using GIS Techniques
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An integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In a

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Publication Date
Thu Oct 07 2021
Journal Name
Bioremediation Journal
Bioremediation of real-field slaughterhouse wastewater associated with power generation in algae-photosynthetic microbial fuel cell
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Pharmaceutical Negative Results
Evaluation Of Most Common Microorganisms Associated with Ectopic Pregnancy by Real Time PCR Among Iraqi Women
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Publication Date
Wed Sep 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Significance of Salivary miRNA 21 Determined by Real Time PCR in Patients with Squamous Cell Carcinoma
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Background: Salivary biomarkers, a non-invasive alternative method to serum and tissue based biomarkers and it is consider as an effective modality for early diagnosis. Salivary microRNA 21, a nucleotide biomarker, was reported to increase in patients with oral squamous cell carcinoma. This study was conducted to measure the fold change of microRNA 21 in stimulated saliva and to study its association with smoking and occurrence of oral squamous cell carcinoma. Materials and methods: A 20 patients with oral squamous cell carcinoma who used to be smokers was included in addition to 40 control subjects (20 smokers and 20 non- smokers health looking subjects). Stimulated saliva was collected under standardized condition. Salivary microRNA 21 wa

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
NONPARAMETRIC And Semiparametric Bayesian Estimators in survival function analysis
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 Most statistical research generally relies on the study of the behaviour of different phenomena during specific time periods and the use of the results of these studies in the development of appropriate recommendations and decision-making and for the purpose of statistical inference on the parameters of the statistical distribution of life times in  The technical staff of most of the manufacturers in the research units of these companies deals with censored data, the main objective of the study of survival is the need to provide information that is the basis for decision making and must clarify the problem and then the goals and limitations of this study and that  It may have different possibilities to perform the

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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
An Analysis of a Partial Temporary Immunity SIR Epidemic Model with Nonlinear Treatment Rate
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     A partial temporary immunity SIR epidemic model involv nonlinear treatment rate is proposed and studied. The basic reproduction number  is determined. The local and global stability of all equilibria of the model are analyzed. The conditions for occurrence of local bifurcation in the proposed epidemic model are established. Finally, numerical simulation is used to confirm our obtained analytical results and specify the control set of parameters that affect the dynamics of the model.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
STATISTICAL COMPUTATION AND APPLICATION WITH GENERALIZED POISSON DISTRIBUTION
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