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Comparison of Robust Circular S and Circular Least Squares Estimators for Circular Regression Model using Simulation
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In this paper, the Monte-Carlo simulation method was used to compare the robust circular S estimator with the circular Least squares method in the case of no outlier data and in the case of the presence of an outlier in the data through two trends, the first is contaminant with high inflection points that represents contaminant in the circular independent variable, and the second the contaminant in the vertical variable that represents the circular dependent variable using three comparison criteria, the median standard error (Median SE), the median of the mean squares of error (Median MSE), and the median of the mean cosines of the circular residuals (Median A(k)). It was concluded that the method of least squares is better than the methods of the robust circular S method in the case that the data does not contain outlier values because it was recorded the lowest mean criterion, mean squares error (Median MSE), the least median standard error (Median SE) and the largest value of the criterion of the mean cosines of the circular residuals A(K) for all proposed sample sizes (n=20, 50, 100). In the case of the contaminant in the vertical data, it was found that the circular least squares method is not preferred at all contaminant rates and for all sample sizes, and the higher the percentage of contamination in the vertical data, the greater the preference of the validity of estimation methods, where the mean criterion of median squares of error (Median MSE) and criterion of median standard error (Median SE) decrease and the value of the mean criterion of the mean cosines of the circular residuals A(K) increases for all proposed sample sizes. In the case of the contaminant at high lifting points, the circular least squares method is not preferred by a large percentage at all levels of contaminant and for all sample sizes, and the higher the percentage of the contaminant at the lifting points, the greater the preference of the validity estimation methods, so that the mean criterion of mean squares of error (Median MSE) and criterion of median standard error (Median SE) decrease, and the value of the mean criterion increases for the mean cosines of the circular residuals A(K) and for all sample sizes.

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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
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
Sun Dec 01 2019
Journal Name
2019 First International Conference Of Computer And Applied Sciences (cas)
A Comparison for Some of the estimation methods of the Parallel Stress-Strength model In the case of Inverse Rayleigh Distribution
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Publication Date
Wed Nov 20 2019
Journal Name
Proceedings Of The 2019 3rd International Conference On Big Data Research
Pressure Vessel Design Simulation Using Hybrid Harmony Search Algorithm
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Publication Date
Tue Jan 01 2019
Journal Name
Spe Europec Featured At 81st Eage Conference And Exhibition
Development of Artificial Neural Networks and Multiple Regression Analysis for Estimating of Formation Permeability
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Publication Date
Fri May 03 2024
Journal Name
Journal Of Optics
Transmission Of 10 Gb/s For Underwater Optical Wireless Communication System
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Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Seemingly Unrelated Regression Model to Measure the Profitability of Some Iraqi Private Commercial Banks with Presence of Outliers
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A seemingly uncorrelated regression (SUR) model is a special case of multivariate models, in which the error terms in these equations are contemporaneously related. The method estimator (GLS) is efficient because it takes into account the covariance structure of errors, but it is also very sensitive to outliers. The robust SUR estimator can dealing outliers. We propose two robust methods for calculating the estimator, which are (S-Estimations, and FastSUR). We find that it significantly improved the quality of SUR model estimates. In addition, the results gave the FastSUR method superiority over the S method in dealing with outliers contained in the data set, as it has lower (MSE and RMSE) and higher (R-Squared and R-Square Adjus

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Publication Date
Mon Oct 01 2018
Journal Name
Al–bahith Al–a'alami
President Trump›s media discourse in the US election Study in electronic news sites - CNN ARABIC Model
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The letter is defined as a message directed by the sender to another party, the future. The aim is to convey, clarify or explain a particular point or subject, and in the form of direct oral communication through speech that contains a set of words and words, The future can discuss the sender directly to exchange ideas with each other, or it may be written and in this case does not require direct interaction between the matchmaker and the recipient. As a result of the different sources and topics of the discourse, and the different types of categories addressed to the speech, and the number, it has been divided into several types.
And schools of discourse analysis emerged in the early eighties of the last century and has spread and ha

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Estimate Kernel Ridge Regression Function in Multiple Regression
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             In general, researchers and statisticians in particular have been usually used non-parametric regression models when the parametric methods failed to fulfillment their aim to analyze the models  precisely. In this case the parametic methods are useless so they turn to non-parametric methods for its easiness in programming. Non-parametric methods can also used to assume the parametric regression model for subsequent use. Moreover, as an advantage of using non-parametric methods is to solve the problem of Multi-Colinearity between explanatory variables combined with nonlinear data. This problem can be solved by using kernel ridge regression which depend o

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Evaluation of ANFIS and Regression Techniques in Estimating Soil Compression Index for Cohesive soils
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Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regre

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