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Comparison of some methods for estimating the parameters of the binary logistic regression model using the genetic algorithm with practical application
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Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the number parameters , and to find estimate the parameters using the numerical methods, sometimes does not give optimum solution because it depends on the initial estimators.

   Some standard methods have been proposed and employed after modifying them by using the genetic algorithm approach in estimation to suit the estimation of  the parameters of this of nonlinear regression models, and then making a comparison between two types of the important estimation methods including the standard estimation methods which included the maximum likelihood method, minimum chi-square method, and improved estimation methods developed which by the researcher which included genetic algorithm method depending on the technique estimates , genetic algorithm method depending on the technique estimates , to choose the best method of estimation by default values to estimate parameter multi-linear regression model a method ols and then convert values the real to standardized and different samples sizes during simulation and by using the statistical criteria Mean Squares Error (MSE) for estimators.

    The method is found to be the best one in the first place one among the standard estimation methods, and  method is the best among the important estimation methods for the purpose of estimating the parameters for binary logistic regression model because it has less (MSE) for estimators compared to other methods.

    In the practical side of this study, this model has been used for modeling the own data infected heart disease and estimating the parameters using the method, reached in it by comparing reasons for cases of occurrence death the real with reasons for cases of occurrence death for the estimated to the appropriate model in the modeling of this type of data and extraction the main cause of death is smoking and also the accuracy of the  method in estimating the parameters of the model.

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The impact of monetary policy variables inflation in Algeria: standard study using self regression time gaps
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                In the past years, the Algerian Economy has witnessed various monetary developments characterized by different monetary and banking reforms aimed by monetary authorities to achieve monetary stability and driving overall growth. It should be noted that there is evidence to initiate fundamental changes on the basis of which new monetary, financing and banking policy mechanisms must be formulated in Algeria by enhancing the pursuit of reforming the monetary system, in order to improve monetary and economic indicators.

                The study a

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Publication Date
Thu Jan 16 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison of some reliability estimation methods for Laplace distribution using simulations
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In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

Publication Date
Tue Oct 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Robust M Estimate With Cubic Smoothing Splines For Time-Varying Coefficient Model For Balance Longitudinal Data
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In this research، a comparison has been made between the robust estimators of (M) for the Cubic Smoothing Splines technique، to avoid the problem of abnormality in data or contamination of error، and the traditional estimation method of Cubic Smoothing Splines technique by using two criteria of differentiation which are (MADE، WASE) for different sample sizes and disparity levels to estimate the chronologically different coefficients functions for the balanced longitudinal data which are characterized by observations obtained through (n) from the independent subjects، each one of them is measured repeatedly by group of  specific time points (m)،since the frequent measurements within the subjects are almost connected an

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Nelson-Olson Method and Two-Stage Limited Dependent Variables (2SLDV ) Method for the Estimation of a Simultaneous Equations System (Tobit Model)
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This study relates to  the estimation of  a simultaneous equations system for the Tobit model where the dependent variables  ( )  are limited, and this will affect the method to choose the good estimator. So, we will use new estimations methods  different from the classical methods, which if used in such a case, will produce biased and inconsistent estimators which is (Nelson-Olson) method  and  Two- Stage limited dependent variables(2SLDV) method  to get of estimators that hold characteristics the good estimator .

That is , parameters will be estim

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Compared of estimating two methods for nonparametric function to cluster data for the white blood cells to leukemia patients
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Abstract:                                        

   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelate

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Four Level Prior Distributions
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Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
About Semi-parametric Methodology for Fuzzy Quantile Regression Model Estimation: A Review
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In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce

Paper Type: Review article.

another suggestion based on artificial neural networks.

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of The College Of Languages (jcl)
The Influence of Manipulating the Virtual Library in Comparison with the Individual Learning via Computer Use in English Language
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The study aims at investigating the effectiveness of the Virtual Library Technology, in developing the achievement of the English Language Skills in the Center of Development and Continuous Education, in comparison with the individual learning via personal computer to investigate the students' attitude towards the use of both approaches. The population of the study includes the participants in the English Language course arranged in the Center. The sample includes 60 students who were randomly chosen from the whole population (participants in English Courses for the year 2009-2010). The sample is randomly chosen and divided into two experimental groups. The first group has learned through classroom technology; while the other group has l

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Selection of the initial value of the time series generating the first-order self-regression model in simulation modeAnd their impact on the accuracy of the model
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In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method  and the least squares method and that using the method of simulation model  first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.

                  

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Genetic Algorithm Optimization Model for Central Marches Restoration Flows with Different Water Quality Scenarios
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A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and

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