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Bayesian Tobit Quantile Regression Model Using Double Adaptive elastic net and Adaptive Ridge Regression
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     Recently Tobit  Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique  and Bayesian hierarchical model with adaptive ridge regression technique .

 in double adaptive elastic net technique we assume  different penalization parameters  for penalization different regression coefficients in both parameters λ1and  λ, also in adaptive ridge regression technique we assume different  penalization parameters for penalization different regression coefficients in parameter λ . 

Simulation study  was used for explain the efficiency of the proposed methods .The result illustrated the efficiency  of the proposed methods for dealing with the estimation of parameters model in present of high correlation in explanatory variables    .

       This is the first work that is discussing the parameter  estimation  in TQR model with double adaptive elastic net and adaptive ridge regression.

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Publication Date
Sat Dec 01 2018
Journal Name
Swarm And Evolutionary Computation
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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Publication Date
Fri Dec 09 2016
Journal Name
Éditions Universitaires EuropÉennes Est Gestionée Par Omniscriptum Management Gmbh
Adaptive Modeling of Urban Dynamics With Mobile Phone Database
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The communication networks (mobile phone networks, social media platforms) produce digital traces from their usages. This type of information help to understand and analyze the human mobility in very accurate way. By these analyzes over cities, it can give powerful data on daily citizen activities, urban planners have in that way, relevant indications for decision making on design and development. As well as, the Call detail Records (CDRs) provides valuable spatiotemporal data at the level of citywide or even nationwide. The CDRs could be analyzed to extract the life patterns and individuals mobility in an observed urban area and during ephemeral events. Whereas, their analysis gives conceptual views about human density and mobility pattern

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
An Improved Adaptive Spiral Dynamic Algorithm for Global Optimization
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This paper proposes a new strategy to enhance the performance and accuracy of the Spiral dynamic algorithm (SDA) for use in solving real-world problems by hybridizing the SDA with the Bacterial Foraging optimization algorithm (BFA). The dynamic step size of SDA makes it a useful exploitation approach. However, it has limited exploration throughout the diversification phase, which results in getting trapped at local optima. The optimal initialization position for the SDA algorithm has been determined with the help of the chemotactic strategy of the BFA optimization algorithm, which has been utilized to improve the exploration approach of the SDA. The proposed Hybrid Adaptive Spiral Dynamic Bacterial Foraging (HASDBF)

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Compare between simex and Quassi-likelihood methods in estimation of regression function in the presence of measurement error
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       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Estimates Nonparametric In Multiple Regression Analysis Function (Gamma ,Beta)
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The use of non-parametric models and subsequent estimation methods requires that many of the initial conditions that must be met to represent those models of society under study are appropriate, prompting researchers to look for more flexible models, which are represented by non-parametric models                  

          In this study, the most important and most widespread estimations of the estimation of the nonlinear regression function were investigated using Nadaraya-Watson and Regression Local Ploynomial, which are one of the types of non-linear

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Slice inverse regression with the principal components in reducing high-dimensions data by using simulation
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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

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Institutional Performance Assessment using a model of the European Foundation for Quality Management (EFQM) A case study at an organization
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The study aims to use the European Excellence Model (EFQM) in assessing the institutional performance of the National Center for Administrative Development and Information Technology in order to determine the gap between the actual reality of the performance of the Center and the standards adopted in the model, in order to know the extent to which the Center seeks to achieve excellence in performance to improve the level of services provided and the adoption of methods Modern and contemporary management in the evaluation of its institutional performance.

The problem of the study was the absence of an institutional performance evaluation system at the centre whereby weaknesses (areas of improvement) and st

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Publication Date
Wed May 01 2024
Journal Name
Heliyon
Determining the bacterial and viral meningitis trend in Iraq from 2007 till 2023 using joinpoint regression
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Publication Date
Mon Feb 01 2021
Journal Name
Https://www.researchgate.net/journal/university-of-baghdad-engineering-journal-1726-4073
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very

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