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Some Methods to Estimate the Parameters of Generalized Exponential Rayleigh Model by Simulation
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This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
USE OF MODIFIED MAXIMUM LIKELIHOOD METHOD TO ESTIMATE PARAMETERS OF THE MULTIPLE LINEAR REGRESSION MODEL
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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
The use of the Principal components and Partial least squares methods to estimate the parameters of the logistic regression model in the case of linear multiplication problem
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Abstract

  The logistic regression model is one of the nonlinear models that aims at obtaining highly efficient capabilities, It also the researcher an idea of the effect of the explanatory variable on the binary response variable.                                                                                  &nb

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Publication Date
Sun Dec 01 2019
Journal Name
2019 First International Conference Of Computer And Applied Sciences (cas)
A Comparison for Some of the estimation methods of the Parallel Stress-Strength model In the case of Inverse Rayleigh Distribution
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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
On Shrunken Estimation of Generalized Exponential Distribution
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This paper deal with the estimation of the shape parameter (a) of Generalized Exponential (GE) distribution when the scale parameter (l) is known via preliminary test single stage shrinkage estimator (SSSE) when a prior knowledge (a0) a vailable about the shape parameter as initial value due past experiences as well as suitable region (R) for testing this prior knowledge.

The Expression for the Bias, Mean squared error [MSE] and Relative Efficiency [R.Eff(×)] for the proposed estimator are derived. Numerical results about beha

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian methods to estimate sub - population
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The aim of the research is to estimate the hidden population. Here، the number of drug users in Baghdad was calculated for the male age group (15-60) years old ، based on the Bayesian models. These models are used to treat some of the bias in the Killworth method Accredited in many countries of the world.

Four models were used: random degree، Barrier effects، Transmission bias، the first model being random، an extension of the Killworth model، adding random effects such as variance and uncertainty Through the size of the personal network، and when expanded by adding the fact that the respondents have different tendencies، the mixture of non-random variables with random to produce

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Traffic Simulation of Urban Street to Estimate Capacity
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This research aimed to develop a simulation traffic model for an urban street with heterogeneous traffic capable of analyzing different types of vehicles of static and dynamic characteristics based on trajectory analysis that demonstrated psychophysical driver behavior. The base developed model for urban traffic was performed based on the collected field data for the major urban street in Baghdad city. The parameter; CC1 minimum headway (represented the speed-dependent of the safety distance from stop line that the driver desired) justified in the range from (2.86sec) to (2.17 sec) indicated a good match to reflect the actual traffic behavior for urban traffic streets. A good indication of the convergence between simulat

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the method of partial least squares and the algorithm of singular values decomposion to estimate the parameters of the logistic regression model in the case of the problem of linear multiplicity by using the simulation
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
Comparison between Rush Model Parameters to Completed and Lost Data by Different Methods of Processing Missing Data
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The current study aims to compare between the assessments of the Rush model’s parameters to the missing and completed data in various ways of processing the missing data. To achieve the aim of the present study, the researcher followed the following steps: preparing Philip Carter test for the spatial capacity which consists of (20) items on a group of (250) sixth scientific stage students in the directorates of Baghdad Education at Al–Rusafa (1st, 2nd and 3rd) for the academic year (2018-2019). Then, the researcher relied on a single-parameter model to analyze the data. The researcher used Bilog-mg3 model to check the hypotheses, data and match them with the model. In addition

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economic And Administrative Science
On Shrinkage Estimation for Generalized Exponential Distribution
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Publication Date
Mon Jun 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
On Bayesian Estimation of System Reliability in Stress – Strength Model Based on Generalized Inverse Rayleigh Distribution
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Abstract<p>The parameter and system reliability in stress-strength model are estimated in this paper when the system contains several parallel components that have strengths subjects to common stress in case when the stress and strengths follow Generalized Inverse Rayleigh distribution by using different Bayesian estimation methods. Monte Carlo simulation introduced to compare among the proposal methods based on the Mean squared Error criteria.</p>
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