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jeasiq-2350
Semi Parametric Logistic Regression Model with the Outputs Representing Trapezoidal Intuitionistic Fuzzy Number
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In this paper, the fuzzy logic and the trapezoidal fuzzy intuitionistic number were presented, as well as some properties of the trapezoidal fuzzy intuitionistic number and semi- parametric logistic regression model when using the trapezoidal fuzzy intuitionistic number. The output variable represents the dependent variable sometimes cannot be determined in only two cases (response, non-response)or (success, failure) and more than two responses, especially in medical studies; therefore so, use a semi parametric logistic regression model with the output variable (dependent variable) representing a trapezoidal fuzzy intuitionistic number.

the model was estimated on simulation data when sample sizes 25,50 and 100, as the parametric part was estimated by two methods of estimation, are fuzzy ordinary least squares estimators FOLSE method and suggested fuzzy weighted least squares estimators SFWLSE , while  the non-parametric part is estimated by Nadaraya Watson estimation and Nearest Neighbor estimator. The results were the fuzzy ordinary least squares estimators method was better than the suggested fuzzy weighted least squares estimators while, in the non-parametric portion, the Nadaraya Watson estimators had better than Nearest Neighbor estimators to estimate the model

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare Estimate Methods of Parameter to Scheffʼe Mixture Model By Using Generalized Inverse and The Stepwise Regression procedure for Treatment Multicollinearity Problem
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Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Effect of applying the CAMEL model to profitability of banks )An applied study on a number of Iraqi banks for the period 2010-2016(
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The evaluation of banks plays an important role in maintaining the interests of customers with the bank as well as providing continuous supervision and control by the Central Bank. The Central Bank of Iraq conducted an assessment of the Iraqi banks through the implementation of the CAMEL model during a certain period. This evaluation did not continue. The research provides continuity to the Central Bank's assessment and as a step to continue the evaluation process for all banks through the use of the CAMEL model. ROA and ROE by using the regression model for four Iraqi banks registered in the Iraqi market for securities during the period 2010-2016. The results showed that the capital and profitability indicators have a significan

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Engineering
Designing a Secure Software-Defined Radio Transceiver using the Logistic Map
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The need to exchange large amounts of real-time data is constantly increasing in wireless communication. While traditional radio transceivers are not cost-effective and their components should be integrated, software-defined radio (SDR) ones have opened up a new class of wireless technologies with high security.  This study aims to design an  SDR  transceiver was built using one type of modulation, which is 16 QAM, and adding a  security subsystem using one type of chaos map, which is a  logistic map, because it is a very simple nonlinear dynamical equations that generate a random key and  EXCLUSIVE  OR with the originally transmitted data to protect data through the transmission. At th

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Publication Date
Thu Apr 01 2021
Journal Name
Neuroquantology
Finding Most Stable Isobar for Nuclides with Mass Number (165- 175) against Beta Decay
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In the beta decay process, a neutron converts into a proton, or vice versa, so the atom in this process changes to a more stable isobar. Bethe-Weizsäcker used a quasi-experimental formula in the present study to find the most stable isobar for isobaric groups of mass nuclides (A=165-175). In a group of isobars, there are two methods of calculating the most stable isobar. The most stable isobar represents the lowest parabola value by calculating the binding energy value (B.E) for each nuclide in this family, and then drawing these binding energy values as a function of the atomic number (Z) in order to obtain the mass parabolas, the second method is by calculating the atomic number value of the most stable isobar (ZA). The results show

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Analytical Study Compared Between Poisson and Poisson Hierarchical Model and Applied in Healthy Field
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Through this research, We have tried to evaluate the health programs and their effectiveness in improving the health situation through a study of the health institutions reality in Baghdad to identify the main reasons that affect the increase in maternal mortality by using two regression models, "Poisson's Regression Model" and "Hierarchical Poisson's Regression Model". And the study of that indicator (deaths) was through a comparison between the estimation methods of the used models. The "Maximum Likelihood" method was used to estimate the "Poisson's Regression Model"; whereas the "Full Maximum Likelihood" method were used for the "Hierarchical Poisson's Regression Model

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Publication Date
Wed Dec 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
مقارنة بين طرائق تقدير معالم الانحدار عند وجود مشكلة عدم تجانس التباين مع التطبيق العملي
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In this research weights, which are used, are estimated using General Least Square Estimation to estimate simple linear regression parameters when the depended variable, which is used, consists of two classes attributes variable (for Heteroscedastic problem) depending on Sequential Bayesian Approach instead of the Classical approach used before, Bayes approach provides the mechanism of tackling observations one by one in a sequential way, i .e each new observation will add a new piece of information for estimating the parameter of probability estimation of certain phenomenon of Bernoulli trials who research the depended variable in simple regression  linear equation. in addition to the information deduced from the past exper

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Publication Date
Tue Dec 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Constructing a new mixed probability distribution with fuzzy reliability estimation
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This paper deals with constructing mixed probability distribution from mixing exponential

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Scopus
Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Planning the Production of the Electrical Distribution Converter (400KV/11) Using Time Series Methods and Goal Programming in the Fuzzy Environment
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This Paper aims to plan the production of the electrical distribution converter (400 KV/11) for one month at Diyala Public Company and with more than one goal for the decision-maker in a fuzzy environment. The fuzzy demand was forecasting using the fuzzy time series model. The fuzzy lead time for raw materials involved in the production of the electrical distribution converter (400 KV/11) was addressed using the fuzzy inference matrix through the application of the matrix in Matlab, and since the decision-maker has more than one goal, so a mathematical model of goal programming was create, which aims to achieve two goals, the first is to reduce the total production costs of the electrical distribution converter (400 KV/11) and th

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
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-

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
CALCULATION BIASES FOR COEFFICIENTS AND SCALE PARAMETER FOR LINEAR (TYPE 1) EXTREME VALUE REGRESSION MODEL FOR LARGEST VALUES
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Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

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