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Estimate the Parameters and Related Probability Functions for Data of the Patients of Lymph Glands Cancer via Birnbaum-Saunders Model
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 In this paper,we estimate the parameters and related probability functions, survival function, cumulative distribution function , hazard function(failure rate) and failure  (death) probability function(pdf) for two parameters Birnbaum-Saunders distribution which is fitting the complete data for the patients of  lymph glands cancer. Estimating the parameters (shape and scale) using (maximum likelihood , regression quantile and shrinkage) methods and then compute the value of mentioned related probability  functions depending on sample from real data which describe the duration of survivor for patients who suffer from the lymph glands cancer based on diagnosis of disease or the inter of patients in a hospital for period of three years ( start with 2010 to the end of 2012) .Calculating and estimating all previous probability functions , then comparing the numerical estimation by using statistical indicators mean squares error and mean absolute percentage error between the three considered estimation methods with respect to survival function. Concluding that, the survival function for the lymph glands cancer by using shrinkage method is the best.

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
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Scopus (23)
Scopus
Publication Date
Sun Oct 02 2022
Journal Name
Al-manhaj
Mathematical Statistics - Second Edition
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This Book is the second edition that intended to be textbook studied for undergraduate/ postgraduate course in mathematical statistics. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces events and probability review. Chapter Two devotes to random variables in their two types: discrete and continuous with definitions of probability mass function, probability density function and cumulative distribution function as well. Chapter Three discusses mathematical expectation with its special types such as: moments, moment generating function and other related topics. Chapter Four deals with some special discrete distributions: (Discrete Uniform, Bernoulli, Binomial, Poisson, Geometric, Neg

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