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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
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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Publication Date
Sun Jan 01 2023
Journal Name
Materials Today: Proceedings
Synthesis and characterization of some mixed ligands complexes of β-enaminone with some metal ions
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Publication Date
Mon Jul 09 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ESTIMATION OF WATER POLLUTION AND CULTIVATED PLANTS ON THE DIYALA RIVER WITH HEAVY ELEMENTS DURING THE SUMMER BY FLAME ATOMIC ABSORPTION: ESTIMATION OF WATER POLLUTION AND CULTIVATED PLANTS ON THE DIYALA RIVER WITH HEAVY ELEMENTS DURING THE SUMMER BY FLAME ATOMIC ABSORPTION
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This study was carried out to measure the percentage of heavy metals pollution in the water of the Diyala river and to measure the percentage of contamination of these elements in the leafy vegetables grown on both sides of the Diyala river, which are irrigated by the contaminated river water (celery, radish, lepidium, green onions, beta vulgaris subsp, and malva). Laboratory analysis was achieved to measure the ratio of heavy element contamination (Pb, Fe, Ni, Cd, Zn and Cr) using flame atomic absorption spectrophotometer during the summer months of July and August for the year 2017. The study showed that the elements of zinc, chromium, nickel and cadmium were high concentrations and exceeded. The maximum concentration of these

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Publication Date
Tue Jul 01 2025
Journal Name
Iet Conference Proceedings
Spatial quantile autoregressive model with application to poverty rates in the districts of Iraq
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This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro

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Publication Date
Sat Jan 19 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
USING PROBABILITY REGRESSION MODELS TO MEASURING MANAGEMENT EFFICIENCY FOR BROILER PROJECTS
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The efficiency of management is determining factor for the success or failure of agricultural projects generally and Livestock particularly achieving its objectives. Therefore, this research came to diagnose the most important variables that determine the efficiency of management using the probability regression models to measure the probability of management efficient of broilers production projects using  random sample included (60) broilers projects represented 11.6% of Baghdad province (research community) in 2016. After estimating the relationship between the management efficiency (descriptive dependent variable) and the independent variables affecting it (age, educational level, production index (PI), experience). The results

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Estimates Nonparametric In Multiple Regression Analysis Function (Gamma ,Beta)
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The use of non-parametric models and subsequent estimation methods requires that many of the initial conditions that must be met to represent those models of society under study are appropriate, prompting researchers to look for more flexible models, which are represented by non-parametric models                  

          In this study, the most important and most widespread estimations of the estimation of the nonlinear regression function were investigated using Nadaraya-Watson and Regression Local Ploynomial, which are one of the types of non-linear

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Solution of Nonlinear High Order Multi-Point Boundary Value Problems By Semi-Analytic Technique
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In this paper, we present new algorithm for the solution of the nonlinear high order multi-point boundary value problem with suitable multi boundary conditions. The algorithm is based on the semi-analytic technique and the solutions are calculated in the form of a rapid convergent series. It is observed that the method gives more realistic series solution that converges very rapidly in physical problems. Illustrative examples are provided to demonstrate the efficiency and simplicity of the proposed method in solving this type of multi- point boundary value problems.

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Publication Date
Tue Aug 18 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
THE COMPARISON OF THE METHODS ESTIMATING THE FRACTIONAL DIFFERENCES OF PARAMETER AND ITS DEPENDENCE ON ESTIMATION THE BEST LINEAR MODEL OF TIME SERIES IN THE ENVIRONMENTAL FIELD
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Publication Date
Sat Dec 01 2018
Journal Name
Ibn Al-haitham Jour. For Pure & Appl. Sci.
Estimation of Pentraxin-3(PTX3) in Rheumatoid Arthritis Males’ patients (with and without) Type II Diabetes Mellitus in Iraq
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Rheumatoid arthritis is a chronic inflammatory autoimmune disease its etiology is unknown. The classical autoimmune diseases, have adaptive immune genetic associations with autoantibodies and major histocompatibility complex (MHC) class II such as rheumatoid arthritis (RA), diabetes mellitus type two (DM II). Serum of99 males suffering from RA without DMII as group (G1), 45 males suffering from RA with DM II as group (G2) and 40 healthy males as group (G3) were enrolled in this study to estimation of alkaline phosphates (ALP), C-reactive protein (CRP) and Pentraxin-3(PTX). Results showed a highly significant increase in PTX3 levels in G1 and G2 compared to G3 and a significant decrease in G1comparing to G2. Results also revealed a significa

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Publication Date
Tue Oct 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Between Shrinkage &Maximum likelihood Method For Estimation Parameters &Reliability Function With 3- Parameter Weibull Distribution By Using Simulation
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The 3-parameter Weibull distribution is used as a model for failure since this distribution is proper when the failure rate somewhat high in starting operation and these rates will be decreased with increasing time .

In practical side a comparison was made between (Shrinkage and Maximum likelihood) Estimators for parameter and reliability function using simulation , we conclude that the Shrinkage estimators for parameters are better than maximum likelihood estimators but the maximum likelihood estimator for reliability function is the better using statistical measures (MAPE)and (MSE) and for different sample sizes.

Note:- ns : small sample ; nm=median sample

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