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jeasiq-2351
Semi parametric Estimators for Quantile Model via LASSO and SCAD with Missing Data
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In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Parametric Nonlinear Programming Approach with Fuzzy Queues Using Hexagonal Membership Functions
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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparing Different Estimators for the shape Parameter and the Reliability function of Kumaraswamy Distribution
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In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison between the estimated of nonparametric methods by using the methodology of quantile regression models
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This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of The Association Of Arab Universities For Basic And Applied Sciences
Semi-analytical method for solving Fokker-Planck’s equations
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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Interdisciplinary Mathematics
Semi-analytical iteration techniques for solving differential equations
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The main objective of this work is to use and compare some techniques, namely the variational Iteration method (VIM), Decomposition Method (ADM), Differential Transform Method (DTM), and Temimi and Ansari Method (TAM) for differential equations of the first and second orders that appeared in physics and engineering. Notably, the results indicate that the VIM gives a solution in series form, which converges to an exact solution;. At the same time, DTM is easy to apply but requires transformation, ADM does not need any transformation except the calculation of Adomain polynomials. TAM solved nonlinear problems in much easier iteration steps, which converge to the true solution without applying any assumption. The results obtained conve

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Estimating Stock Returns Using Rough Set Theory: An Exploratory study With An Evidence From Iraq Stock Exchange
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‎ This research aims to estimate stock returns, according to the ‎Rough Set Theory ‎approach, ‎test ‎its effectiveness and accuracy in predicting stock returns and their potential in the ‎field of ‎financial ‎markets, and rationalize investor decisions. The research sample is totaling (10) ‎companies traded at Iraq Stock Exchange. The results showed a remarkable ‎ ‎Rough Set Theory application in data reduction, contributing to the rationalization of ‎investment ‎decisions. The most prominent conclusions are the capability of rough set theory ‎in ‎dealing with financial data and applying it for forecasting stock ‎returns.‎The ‎research provides those interested in investing stocks in financial

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between the logistic regression model and Linear Discriminant analysis using Principal Component unemployment data for the province of Baghdad
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     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

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Publication Date
Tue Mar 30 2021
Journal Name
Wasit Journal Of Computer And Mathematics Science
Dynamic Data Replication for Higher Availability and Security
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The paradigm and domain of data security is the key point as per the current era in which the data is getting transmitted to multiple channels from multiple sources. The data leakage and security loopholes are enormous and there is need to enforce the higher levels of security, privacy and integrity. Such sections incorporate e-administration, long range interpersonal communication, internet business, transportation, coordinations, proficient correspondences and numerous others. The work on security and trustworthiness is very conspicuous in the systems based situations and the private based condition. This examination original copy is exhibiting the efficacious use of security based methodology towards the execution with blockchain

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
A Modified Approach by Using Prediction to Build a Best Threshold in ARX Model with Practical Application
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The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

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Publication Date
Mon Feb 22 2021
Journal Name
Educatum Journal Of Science, Mathematics And Technology
Effect of ammonia/gallium ratio and growth temperature towards the surface morphology of semi-polar GaN grown on m-plane sapphire via MOCVD
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A single-crystalline semi-polar gallium nitride (11-22) was grown on m-plane (10-10) sapphire substrate by metal organic chemical vapor deposition. Three-step approach was introduced to investigate the grain size evolution for semi-polar (11-22) GaN. Such approach was achieved due to the optimized gallium to ammonia ratio and temperature variations, which led to high quality (11-22) oriented gallium nitride epilayers. The full width at half maximum values along (-1-123) and (1-100) planes for the overgrowth temperature of 1080°C were found to be as low as 0.37° and 0.49°, respectively. This was an indication of the enhanced coalescence and reduction in root mean square roughness as seen by atomic force microscopy. Surface analysi

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