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Robust Two-Step Estimation and Approximation Local Polynomial Kernel For Time-Varying Coefficient Model With Balance Longitudinal Data
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      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-steps method depends, in estimation, on (OLS) method, which is sensitive for the existence of abnormality in data or contamination of error; robust methods have been proposed such as LAD & M to strengthen the two-steps method towards the abnormality and contamination of error. In this research imitating experiments have been performed, with verifying the performance of the traditional and robust methods for Local Linear kernel LLPK technique by using two criteria, for different sample sizes and disparity levels.

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Publication Date
Mon Dec 08 2025
Journal Name
Journal Of Administration And Economics
Bayesian Method in Classification Regression Tree to estimate nonparametric additive model compared with Logistic Model with Application
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The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

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Publication Date
Fri Oct 01 2021
Journal Name
International Journal Of Mechanical Engineering And Robotics Research
Proportional-Derivative PD Vibration Control with Adaptive Approximation Compensator for a Nonlinear Smart Thin Beam Interacting with Fluid
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This work is concerned with the vibration attenuation of a smart beam interacting with fluid using proportional-derivative PD control and adaptive approximation compensator AAC. The role of the AAC is to improve the PD performance by compensating for unmodelled dynamics using the concept of function approximation technique FAT. The key idea is to represent the unknown parameters using the weighting coefficient and basis function matrices/vectors. The weighting coefficient vector is updated using Lyapunov theory. This controller is applied to a flexible beam provided with surface bonded piezo-patches while the vibrating beam system is submerged in a fluid. Two main effects are considered: 1) axial stretching of the vibrating beam that leads

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
A Comparative Study for Estimate Fractional Parameter of ARFIMA Model
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      Long memory analysis is one of the most active areas in econometrics and time series where various methods have been introduced to identify and estimate the long memory parameter in partially integrated time series. One of the most common models used to represent time series that have a long memory is the ARFIMA (Auto Regressive Fractional Integration Moving Average Model) which diffs are a fractional number called the fractional parameter. To analyze and determine the ARFIMA model, the fractal parameter must be estimated. There are many methods for fractional parameter estimation. In this research, the estimation methods were divided into indirect methods, where the Hurst parameter is estimated fir

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Publication Date
Sat Aug 24 2024
Journal Name
Mathematics
Identification of Time-Wise Thermal Diffusivity, Advection Velocity on the Free-Boundary Inverse Coefficient Problem
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This paper is concerned with finding solutions to free-boundary inverse coefficient problems. Mathematically, we handle a one-dimensional non-homogeneous heat equation subject to initial and boundary conditions as well as non-localized integral observations of zeroth and first-order heat momentum. The direct problem is solved for the temperature distribution and the non-localized integral measurements using the Crank–Nicolson finite difference method. The inverse problem is solved by simultaneously finding the temperature distribution, the time-dependent free-boundary function indicating the location of the moving interface, and the time-wise thermal diffusivity or advection velocities. We reformulate the inverse problem as a non-

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Analyzing current and future direction of non-oil primary balance: Case Study of Iraq Using Exponential Smoothing model
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In recent years, non-oil primary balance indicator has been given considerable financial important in rentier state. It highly depends on this indicator to afford a clear and proper picture of public finance situation in term of appropriate and sustainability in these countries, due to it excludes the effect of oil- rental from compound of financial accounts which provide sufficient information to economic policy makers of how economy is able to create potential added value and then changes by eliminating one sided shades of economy. In Iraq, since, 2004, the deficit in value of this indicator has increased, due to almost complete dependence on the revenues of the oil to finance the budget and the obvious decline of the non-oil s

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Ordinary Methods (LS,IV) and Robust Methods (2SWLS,LTS,RA) to estimate the Parameters of ARX(1,1,1) Model for Electric Loads
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Abstract:

The models of time series often suffer from the problem of the existence of outliers ​​that accompany the data collection process for many reasons, their existence may have a significant impact on the estimation of the parameters of the studied model. Access to highly efficient estimators  is one of the most important stages of statistical analysis, And it is therefore important to choose the appropriate methods to obtain good  estimators. The aim of this research is to compare the ordinary estimators and the robust estimators of the estimation of the parameters of

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Notes on estimation of ARMA model (1.1) And ARMA (0,1)
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By driven the moment estimator of ARMA (1, 1) and by using the simulation some important notice are founded, From the more notice conclusions that the relation between the sign   and moment estimator for ARMA (1, 1) model that is: when the sign is positive means the root      gives invertible model and when the sign is negative means the root      gives invertible model. An alternative method has been suggested for ARMA (0, 1) model can be suitable when

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Fri Sep 20 2019
Journal Name
Journal Of The College Of Education For Women
History of Local Reprimands in the Northwest Caucasus from Ancient Times to the 19th century
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Ubikh is one of the most important tribes of the Northwest Caucasus and has a long history. Naturally, rebukes are an integral part of the Caucasus region. Their people were able to confront the Russian invasion of their lands like the rest of the Caucasus tribes to defend their existence, freedom and the right to build their independent state, but they were not able to resist the great Russian military progress they achieved on all sides. For the territory that belonged to Persia and the Ottoman Empire and ended the resistance of the Meridian movement in the Northeast Caucasus, the Russians left only the weak resistance of the tribes of the Northwest Caucasus led by the rebuke after Russia managed to eliminate all resistance movements i

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Analysis of concrete beams reinforced by GFRP bars with varying parameters
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Abstract<p>Structural buildings consist of concrete and steel, and these buildings have confronted many challenges from various aggressive environments against the materials manufactured from them. It contains high water levels and buildings whose concrete cover may be damaged and thus lead to the deterioration and corrosion of steel. It was important to have an alternative to steel, such as the glass fiber reinforced polymer (GFRP), which is distinguished by its great effectiveness in resisting corrosion, as well as its strong tensile resistance. Still, one of its drawbacks is that it has a low modulus of elasticity. This research article aims to conduct a numerical study using the nonlinear fi</p> ... Show More
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