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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 Apr 01 2015
Journal Name
2015 Annual Ieee Systems Conference (syscon) Proceedings
Automatic generation of fuzzy classification rules using granulation-based adaptive clustering
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Publication Date
Sun May 01 2016
Journal Name
International Journal Of Computer Applications
Lossless Image Compression using Adaptive Predictive Coding of Selected Seed Values
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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare some wavelet estimators for parameters in the linear regression model with errors follows ARFIMA model.
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The aim of this research is to estimate the parameters of the linear regression model with errors following ARFIMA model by using wavelet method depending on maximum likelihood and approaching general least square as well as ordinary least square. We use the estimators in practical application on real data, which were the monthly data of Inflation and Dollar exchange rate obtained from the (CSO) Central Statistical organization for the period from 1/2005 to 12/2015. The results proved that (WML) was the most reliable and efficient from the other estimators, also the results provide that the changing of fractional difference parameter (d) doesn’t effect on the results.

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Publication Date
Sat Dec 31 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimation of nonparametric regression function using shrinkage wavelet and different mother functions
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Thu Dec 12 2013
Journal Name
Iraqi Journal Of Science
Determination of Optimum Mechanical Drilling Parameters for an Iraqi Field with Regression Model
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Publication Date
Tue Apr 04 2023
Journal Name
Journal Of Techniques
Comparison Between the Kernel Functions Used in Estimating the Fuzzy Regression Discontinuous Model
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Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

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Publication Date
Thu May 28 2026
Journal Name
Al Kut Journal Of Economics And Administrative Sciences
Use of the Bootstrap in the logistic regression model for Breast cancer disease
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The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

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