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Use Generalized Pareto Survival Models to Estimation Optimal Survival Time for Myocardial Infarction Patients
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The survival analysis is one of the modern methods of analysis that is based on the fact that the dependent variable represents time until the event concerned in the study. There are many survival models that deal with the impact of explanatory factors on the likelihood of survival, including the models proposed by the world, David Cox, one of the most important and common models of survival, where it consists of two functions, one of which is a parametric function that does not depend on the survival time and the other a nonparametric function that depends on times of survival, which the Cox model is defined as a semi parametric model, The set of parametric models that depend on the time-to-event distribution parameters such as Exponential Model, Weibull Model, Log-logistic Model. Our research aims to adopt some of the Bayesian Optimal Criteria in achieving optimal design to estimate the optimal survival time for patients with myocardial infarction by constructing a parametric survival model based on the probability distribution of the survival times of myocardial infarction patients, which is among the most serious diseases that  threaten human life and the main cause of death all over the world, as the duration of survival of patients with myocardial infarction varies with the factor or factors causing the injury, there are many factors that lead to the disease such as diabetes, high blood pressure, high cholesterol, psychological pressure and obesity. Therefore, the need to estimate the optimal survival time was expressed by constructing a model of the relationship between the factors leading to the disease and the patient survival time, and we found that the optimal rate of survival time is 18 days.

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Proposal of Using Principle of Maximizing Entropy of Generalized Gamma Distribution to Estimate the Survival probabilities of the Population in Iraq
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In this research we been estimated the survival function for data suffer from the disturbances and confusion of Iraq Household Socio-Economic Survey: IHSES II 2012 , to data from a five-year age groups follow the distribution of the Generalized Gamma: GG. It had been used two methods for the purposes of estimating and fitting which is the way the Principle of Maximizing Entropy: POME, and method of booting to nonparametric smoothing function for Kernel, to overcome the mathematical problems plaguing integrals contained in this distribution in particular of the integration of the incomplete gamma function, along with the use of traditional way in which is the Maximum Likelihood: ML. Where the comparison on the basis of the method of the Cen

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Publication Date
Tue Apr 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Parametric Models in Survival Analysis for Lung Cancer Patients
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    The aim of this study is to estimate the survival function for the data of lung cancer patients, using parametric methods (Weibull, Gumbel, exponential and log-logistic).

Comparisons between the proposed estimation method have been performed using statistical indicator Akaike information Criterion, Akaike information criterion corrected and Bayesian information Criterion, concluding that the survival function for the lung cancer by using Gumbel distribution model is the best. The expected values of the survival function of all estimation methods that are proposed in this study have been decreasing gradually with increasing failure times for lung cancer patients, which means that there is an opposite relationshi

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING OF TIME-VARYING ESTIMATION FOR DISCRETE SURVIVAL ANALYSIS FOR DIALYSIS PATIENTS IN BASRAH, IRAQ
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Survival analysis is widely applied to data that described by the length of time until the occurrence of an event under interest such as death or other important events. The purpose of this paper is to use the dynamic methodology which provides a flexible method, especially in the analysis of discrete survival time, to estimate the effect of covariate variables through time in the survival analysis on dialysis patients with kidney failure until death occurs. Where the estimations process is completely based on the Bayes approach by using two estimation methods: the maximum A Posterior (MAP) involved with Iteratively Weighted Kalman Filter Smoothing (IWKFS) and in combination with the Expectation Maximization (EM) algorithm. While the other

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Some NONPARAMETRIC ESTIMATORS FOR RIGHT CENSORED SURVIVAL DATA
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The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible parametric models and these models were nonparametric, many researchers, are interested in the study of the function of permanence and its estimation methods, one of these non-parametric methods.

For work of purpose statistical inference parameters around the statistical distribution for life times which censored data , on the experimental section of this thesis has been the comparison of non-parametric methods of permanence function, the existence

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Probabilistic Inventory Models With Pareto Distribution
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Inventory or inventories are stocks of goods being held for future use or sale. The demand for a product in is the number of units that will need to be removed from inventory for use or sale during a specific period. If the demand for future periods can be predicted with considerable precision, it will be reasonable to use an inventory rule that assumes that all predictions will always be completely accurate. This is the case where we say that demand is deterministic.

The timing of an order can be periodic (placing an order every days) or perpetual (placing an order whenever the inventory declines to units).

in this research we discuss how to  formulating inv

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Survival estimation for singly type one censored sample based on generalized Rayleigh distribution
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This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.

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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 Apr 02 2017
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Evaluation of Myocardial Function in Cases of Gestational Hypertension Using Myocardial Performance Index
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Background: Gestational hypertension represents a transient period of elevated blood pressure with  special effects on the maternal left ventricle that is different from the effects observed in chronic essential   hypertension; it affects a previously normal heart and lasts for a maximum of nine months associated with   volume and pressure overload on the maternal heart. Tei index (also called myocardial performance index)   was found to be a dependent combined index evaluating the systolic and diastolic function of the left   ventricle and represents a sensitive indicator for many types of heart diseases.
Objective: to evaluate the effects of gestational hypertension on the maternal myocar

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Woman's Quest for Survival: Margret Drabble's The Millstone
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This study deals with The Millstone (1965) which is a dramatic depiction of a single
mother heroine in a classic predicament. This novel is considered as representative of the age
in which it was written. The primary theme is her intense preoccupation with questions of
fatalism and will. The work also involves, both explicitly and implicitly, feminist concerns.
Because the central protagonist is a woman and the society in which she lives is depicted,
accurately, as deeply patriarchal and class-bound, the problem of the individual's capacity for
self-determination is inevitably tied to the feminist perspective.

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Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of the parameter of the Pareto distribution manual Using the general mediator estimator
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Estimation of the tail index parameter of a one - parameter Pareto model has wide important by the researchers because it has awide application in the econometrics science and reliability theorem.

Here we introduce anew estimator of "generalized median" type and compare it with the methods of Moments and Maximum likelihood by using the criteria, mean square error.

 The estimator of generalized median type performing best over all.

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