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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 Mar 30 2026
Journal Name
Iraqi Journal Of Science
A modified time series model using conditional and unconditional estimations with applications to a real dataset
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Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan

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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
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Estimation of Parameters for the Gumbel Type-I Distribution under Type-II Censoring Scheme
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This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

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Publication Date
Wed Jul 01 2026
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
New Method for Estimation Mebeverine Hydrochloride Drugs Preparation by a New Analyser: Ayah 6S.X1(WSLEDs)-T.- Two Solar Cells Complied with C.F.I.A
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A sensitivity-turbidimetric method at (0-180o) was used for detn. of mebeverine in drugs by two solar cell and six source  with C.F.I.A.. The method was based on the formation  of  ion pair for the pinkish banana color  precipitate by the reaction of Mebeverine hydrochloride with Phosphotungstic acid. Turbidity was measured via the reflection of incident light that collides on the surface particles of   precipitated at 0-180o. All variables were optimized. The linearity ranged of Mebeverine hydrochloride was 0.05-12.5mmol.L-1, the L.D. (S/N= 3)(3SB) was 521.92 ng/sample depending on dilution for the minimum concentration , with correlation coefficient r = 0.9966while was R.S.D%

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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
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Development prediction algorithm of vehicle travel time based traffic data
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This work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera

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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
Thu Jun 16 2022
Journal Name
Al-khwarizmi Engineering Journal
Intelligent Tuning Control of two Link Flexible Manipulator with Piezoelectric Actuator
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This paper represents an experimental study on the application of smart control represented by the use of the fuzzy logic controller. Two-link flexible manipulators that are used in airspace and military applications are made of flexible materials characterized by low frequency and damping ratio. To solve this problem, this paper proposes the use of smart materials (piezoelectric transducers), where each link is bonded with a pair of piezoelectric transducers that act as a sensor and another as an actuator. As the arm vibrates because of the movement generated by the motor, this voltage is controlled by a regulator inside the LABVIEW® 2020 software and sends the output control voltage to the piezoelectric actuator. Experimental results

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Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Estimation of SNR Including Quantization Error of Multi-Wavelength Lidar Receiver
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 This paper comprises the design and operation of mono-static backscatter lidar station based on a pulsed Nd: YAG laser that operates at multiple wavelengths. The three-color lidar laser transmitter is based on the collinear fundamental 1064 nm, second harmonic 532 nm and a third harmonic 355nm output of a Nd:YAG laser. The most important parameter of lidar especially daytime operations is the signal-to-noise ratio (SNR) which gives some instructions in designing of lidar and it is often limit the effective range. The reason is that noises or interferences always badly affect the measured results. The inversion algorithms have been developed for the study of atmospheric aerosols. Signal-to-noise ratio (SNR) of three-color channel re

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