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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
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Quality Function Deployment in Evaluating The Product Applied Research in General Company For Vegetable Oil Industry- Al-M'amoon Factory
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The Quality  function deployment (QFD)  tool is an important  tool of total quality management because its a link between two important parts customer and production process of the product, using advanced House of quality, which contributed to provide more details about improving the product before it had a vision for the future of the product be improved. Also the identification of the two competitors (Alwazeer , Altouri) bases on the survey of retailers  which they identified five competitors products (Alwazeer , Altouri , Ferry , Jif , Dina)for the product (Zahi). Then House of quality  to product (Zahi) has been developed  By using a Kano Model  to classify of customer's requirements for the

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Publication Date
Tue Jun 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
دراسة مقارنة بين بعض الطرائق الحصينة في تقدير معلمات انموذج الانحدار الخطي باستخدام اسلوب المحاكاة التجريبي في حالة وجود بيانات تتضمن مشاهدات شاذة
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In linear regression, an outlier is an observation with large residual.  In other words, it is an observation whose dependent-variable value is unusual given its values on the predictor variables. An outlier observation may indicate a data entry error or other problem.

An observation with an extreme value on a predictor variable is a point with high leverage. Leverage is a measure of how far an independent variable deviates from its mean. These leverage points can have an effect on the estimate of regression coefficients.

Robust estimation for regression parameters deals with cases that have very high leverage, and cases that are outliers. Robust estimation is essentially a

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparison for estimation methods for the autoregressive approximations
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Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

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