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bsj-7962
Estimating the Parameters of Exponential-Rayleigh Distribution under Type-I Censored Data
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     This paper discusses estimating the two scale parameters of Exponential-Rayleigh distribution for singly type one censored data which is one of the most important Rights censored data, using the maximum likelihood estimation method (MLEM) which is one of the most popular and widely used classic methods, based on an iterative procedure such as the Newton-Raphson to find estimated values for these two scale parameters by using real data for COVID-19 was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. The duration of the study was in the interval 4/5/2020 until 31/8/2020 equivalent to 120 days, where the number of patients who entered the (study) hospital with sample size is (n=785). The number of patients who died during the period of study was (m=88). And the number of patients who survived during the study period was (n-m=697), then utilized one of the most important non-parametric tests which is the Chi-square test to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). then, after estimating the parameters of ER distribution for singly type-I censoring data, compute the survival function, hazard function, and probability density function.

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Publication Date
Wed Jun 04 2014
Journal Name
مجلة كلية مدينة العلم الجامعة
تقدير دالة المعولية بالطرائق اللامعلمية في حالة البيانات المراقبة "المتجمعة"
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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Compare to the conditional logistic regression models with fixed and mixed effects for longitudinal data
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Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

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Publication Date
Sun Nov 01 2020
Journal Name
2020 8th Ieee Ras/embs International Conference For Biomedical Robotics And Biomechatronics (biorob)
Estimating Wrist Joint Torque Using Regression Ensemble of Bagged Trees under Multiple Wrist Postures
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Publication Date
Sun Jun 30 2024
Journal Name
Wasit Journal For Pure Sciences
Design Polynomial IIR Digital Filters of the Integer Parameters Space Use to Compress Image Data
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Polynomial IIR digital filters play a crucial role in the process of image data compression. The main purpose of designing polynomial IIR digital filters of the integer parameters space and introduce efficient filters to compress image data using a singular value decomposition algorithm. The proposed work is designed to break down the complex topic into bite-sized pieces of image data compression through the lens of compression image data using Infinite Impulse Response Filters. The frequency response of the filters is measured using a real signal with an automated panoramic measuring system developed in the virtual instrument environment. The analysis of the output signal showed that there are no limit cycles with a maximum radius

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Choosing the best method for estimating the survival function of inverse Gompertz distribution by using Integral mean squares error (IMSE)
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In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

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Publication Date
Mon Mar 01 2010
Journal Name
Al-khwarizmi Engineering Journal
The Effect of Mechanical Combined Contact Stress with Buckling Load on the Stress Distribution in the Ball and Socket Joint Mechanism
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The design of components subjected to contact stress as local compressive stress is important in engineering application especially in ball and socket Joining.  Two kinds of contact stress are introduced in the ball and socket joint, the first is from normal contact while the other is from sliding contact. Although joining two long links (drive shaft in steering cars) will cause the effect of flexural and tensional buckling stress in hollow columns through the ball and socket ends on the failure condition of the joining mechanism. In this paper the consideration of the combined effect of buckling Load and contact stress on the ball and socket joints have been taken, epically on the stress distribution in the contact area. Different

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
new Estimator of the parameter of negative exponential
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the main of this paper is to give a comprehensive presentation of estimating methods namely maximum likelihood bayes and proposed methods for the parameter

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Publication Date
Tue Dec 01 2020
Journal Name
Gulf Economist
The Bayesian Estimation in Competing Risks Analysis for Discrete Survival Data under Dynamic Methodology with Application to Dialysis Patients in Basra/ Iraq
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Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Entrepreneur Decision Making on Ambidexterity Performance: An Applied Research in the Oil Products Distribution Company/ aldawra
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The research aims to determine the role of Entrepreneur decision-making in its dimensions in improving the activities of Ambidexterity performance in its dimensions in the researched company. The importance of the research is also evidenced by assisting the oil products distribution company/session in directing the interest of the researched company because it has a prominent role in the Iraqi industrial community for the Entrepreneur decision-making variable that Contributes to building sustainable competitive advantage. This will happen when the company has an Entrepreneur orientation and a good strategic plan is built by the smart leaders in the researched company The researcher adopted the method of the analyti

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of classical method and optimization methods for estimating parameters in nonlinear ordinary differential equation
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  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es

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