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Detecting Outliers In Multiple Linear Regression
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It is well-known that the existence of outliers in the data will adversely affect the efficiency of estimation and results of the current study. In this paper four methods will be studied to detect outliers for the multiple linear regression model in two cases :  first, in real data; and secondly,  after adding the outliers to data and the attempt to detect it. The study is conducted for samples with different sizes, and uses three measures for  comparing between these methods . These three measures are : the mask, dumping and standard error of the estimate.

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Publication Date
Fri Sep 11 2026
Journal Name
Aip Conference Proceedings
Multiple routes solution of brute force method with ambiguous values in assignment problems
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The evaluation of assignment problems for job suppliers is necessary to meet demands; therefore, academics in the operations research field and management factories have paid considerable attention to assignment problems. Notably, because the central point of classical assignment models with parameters assumes that supplier management oversees all inputs and outputs are fixed data, these types of models cannot provide exact and accurate data. Hence, specific inputs and/or outputs can be improper and ambiguous. Consequently, existing studies have explored various approaches to determine an optimal route that corresponds to assignments to suppliers when ambiguous values are involved. However, the computation of multiple routes for each assign

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Scopus
Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Physics: Conference Series
Bayesian Computational Methods of the Logistic Regression Model
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Abstract<p>In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.</p>
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Publication Date
Mon Jun 22 2015
Journal Name
International Journal Of Industrial Management
Regression Factors of Small Businesses Performance: Conceptual Model
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This study represents an attempt to develop a model that demonstrates the relationship between HRM Practices, Governmental Support and Organizational performance of small businesses. Furthermore, this study assay to unfold the socalled “Black Box” to clarify the ambiguous relationship between HRM practices and organizational performance by considering the pathway of logical sequence influence. The model of this study consists two parts, the first part devoted to examining the causal relationships among HRM practices, employees’ outcomes, and organizational performance. The second part assesses the direct relationship between the governmental support and organizational performance. It is hypothesized that HRM practices positively influ

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Speech Signal Compression Using Wavelet And Linear Predictive Coding
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A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

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Publication Date
Sun Sep 06 2015
Journal Name
Baghdad Science Journal
Oscillations of Third Order Half Linear Neutral Differential Equations
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In this paper the oscillation criterion was investigated for all solutions of the third-order half linear neutral differential equations. Some necessary and sufficient conditions are established for every solution of (a(t)[(x(t)±p(t)x(?(t) ) )^'' ]^? )^'+q(t) x^? (?(t) )=0, t?t_0, to be oscillatory. Examples are given to illustrate our main results.

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Publication Date
Mon Dec 01 2014
Journal Name
Iraqi Journal Of Science,
Detection of human leukocyte antigen and celiac disease auto antibodies in serum of patients with multiple sclerosis
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To determine the important pathogenic role of celiac disease in triggering several autoimmune disease, thirty patients with Multiple Sclerosis of ages (22-55) years have been investigated and compared with 25 healthy individuals. All the studied groups were carried out to measure anti-tissue transglutaminase antibodies IgA IgG by ELISA test, anti-reticulin antibodies IgA and IgG, and anti-endomysial antibodies IgA and IgG by IFAT. There was a significant elevation in the concentration of anti-tissue transglutaminase antibodies IgA and IgG compared to control groups (P≤0.05), there was 4(13.33%) positive results for anti-reticulin antibodies IgA and IgG , 3(10%) positive results for anti-endomysial antibodies IgA and IgG . There were 4 pos

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
THE USE OF SIMULATION AND LINEAR PROGRAMMING IN THE PLANNING OF AUDIT WORK (An Empirical Study in the Office of Financial Supervision)
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Research includes three axes, the first is the average estimate time of achievement (day) to work oversight, to five supervisory departments in the Office of Financial Supervision Federal and then choose the three control outputs and at the level of each of the five departments above, and after analyzing the data statistically back to us that the distribution of the times of achievement It is the exponential distribution (Exponential Distribution) a parameter (q), and the distribution of normal (Normal Distribution) with two parameters (μ, σ2), and introduced four methods of parameter estimation (q) as well as four modalities parameter to estimate (

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Use Of Artificial Neural Networks In Developing The Role Of Auditor In Discovering Fundamental Errors: An Applied Research In General Company for Electrical Industries and Nasr General Company for Mechanical Industries
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Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi

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Publication Date
Mon May 26 2025
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use of Cone Projections and Quadratic programming in Estimation of Constrained Regression
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Statisticians often use regression models like parametric, nonparametric, and semi-parametric models to represent economic and social phenomena. These models explain the relationships between different variables in these phenomena. One of the parametric model techniques is conic projection regression. It helps to find the most important slopes for multidimensional data using prior information about the regression's parameters to estimate the most efficient estimator. R algorithms, written in the R language, simplify this complex method. These algorithms are based on quadratic programming, which makes the estimations more accurate.

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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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