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SUGGESTING MULTIPHASE REGRESSION MODEL ESTIMATION WITH SOME THRESHOLD POINT
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The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of this paper is to suggest a new hybrid estimator obtained by an ad-hoc algorithm which relies on data driven strategy that overcomes outliers. While the minor goal is to introduce a new employment of an unweighted estimation method named "winsorization" which is a good method to get robustness in regression estimation via special technique to reduce the effect of the outliers. Another specific contribution in this paper is to suggest employing "Kernel" function as a new weight (in the scope of the researcher's knowledge).Moreover, two weighted estimations are based on robust weight functions named "Cauchy" and "Talworth". Simulations have been constructed with contamination levels (0%, 5%, and 10%) which associated with sample sizes (n=40,100). Real data application showed the superior performance of the suggested method compared with other methods using RMSE and R2 criteria.

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Estimation of Oxidative Stress and Some Trace Elements in Iraqi Men Patients with Type 2 Diabetes Mellitus
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Type 2 diabetes mellitus (T2DM) is a chronic disorder that is associated with the imbalance of trace elements which are involved in many functions especially enzyme activities. Changes in the levels of serum elements probably can create some complications in type 2 diabetes mellitus.  Previous experimental and clinical studies report that oxidative stress plays a major role in the pathogenesis and development of (T2DM). However, the exact mechanism of oxidative stress could contribute to and accelerate the development of (T2DM).

The aim of this study contained the following sections: firstly, to determine some biochemical parameters in subjects with type 2 diabetes mellitus (T2DM) like lipid peroxidation marker, malondialdeh

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Engineering
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

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Multiphase Flow Behavior Prediction and Optimal Correlation Selection for Vertical Lift Performance in Faihaa Oil Field, Iraq
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In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
IMPROVED IMAGE COMPRESSION BASED WAVELET TRANSFORM AND THRESHOLD ENTROPY
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In this paper, a method is proposed to increase the compression ratio for the color images by
dividing the image into non-overlapping blocks and applying different compression ratio for these
blocks depending on the importance information of the block. In the region that contain important
information the compression ratio is reduced to prevent loss of the information, while in the
smoothness region which has not important information, high compression ratio is used .The
proposed method shows better results when compared with classical methods(wavelet and DCT).

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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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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
USE OF MODIFIED MAXIMUM LIKELIHOOD METHOD TO ESTIMATE PARAMETERS OF THE MULTIPLE LINEAR REGRESSION MODEL
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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between the Methods of Ridge Regression and Liu Type to Estimate the Parameters of the Negative Binomial Regression Model Under Multicollinearity Problem by Using Simulation
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The problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Population Therapeutics And Clinical Pharmacology
Synthesis, Characterization, Biological and Antioxidant estimation of Mixed Schiff Base Ligand and Heterocyclic Compound with Some Metal ions
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In this research, a group of complexes were prepared which were derived from Schiff base ligands, which is called (1E,1'E)-1,1'-(1,2-phenylene)bis(N-(2,4-dichlorophenyl) methanimine) (L) with ortho-phenanthroline (o-phen).The prepared complexes areM(II) [Co(II),Ni(II),Cu(II), Zn(II), Cd(II),and Hg(II)].A range of spectroscopic and technical techniques have been used to characterizethese materials, including:The FTIR, 1H-NMR, LC-Mass Spectrum, UV-Visbale, molar conductance, and magnaticmoment, atomic absorbtion, chlorid contents. Spectral results obtainedare showen that (ortho-phen) and (L) behave as neutral coordinating to the central metal ion by the donatingatoms(N2)of the both compounds. The geometry sha

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Publication Date
Wed Sep 11 2019
Journal Name
Aip Conference Proceedings
Estimation of shock wave position in plasma plume using Sedov-Taylor model
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In this work, radius of shock wave of plasma plume (R) and speed of plasma (U) have been calculated theoretically using Matlab program.