Analyzing Skewed Data with the Epsilon Skew Gamma distribution

Ebtisam Ebtisam Karim Abdulah

doi:10.12785/jsap/020302

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Publication Date

Sat Jun 29 2013

Journal Name

Journal Of Statistics Applications & Probability

Volume

2

Issue Number

No. 3, 195-202

DOI

10.12785/jsap/020302

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Analyzing Skewed Data with the Epsilon Skew Gamma distribution

Skewed Data

Epsilon Skew

Gamma Distribution

Ebtisam Ebtisam Karim Abdulah

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A new distribution, the Epsilon Skew Gamma (ESΓ ) distribution, which was first introduced by Abdulah [1], is used on a near Gamma data. We first redefine the ESΓ distribution, its properties, and characteristics, and then we estimate its parameters using the maximum likelihood and moment estimators. We finally use these estimators to fit the data with the ESΓ distribution

Publication Date

Sun Jun 20 2021

Journal Name

Baghdad Science Journal

Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)

Stress-Strength Model

Inverse Rayleigh Distribution

Least Square Estimator

Maximum Likelihood Method Estimator

Moment method

Uniformly Minimum Variance Unbiased Method

Shrinkage Methods.

Sairan Hamza

Bayda Atiya

Abbas Najim

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In this study, the stress-strength model R = P(Y < X < Z) is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used to estimate the parameters namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.

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Publication Date

Sun Oct 02 2022

Journal Name

Al-manhaj

Mathematical Statistics - Second Edition

Mathematical Expectation

Moment Generating Function

Cumulative Distribution Function

Probability Mass Function

Probability Density Function

Discrete Distributions

Continuous Distributions

Joint distributions

Marginal Distributions

Conditional Distributions

Transformations

Order Statistics.

Omar Abdulmohsin

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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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Publication Date

Sat Oct 01 2016

Journal Name

Journal Of Theoretical And Applied Information Technology

Factors affecting global virtual teams’ performance in software projects

Today the trend is to perform software development work via distributed geographical area among team

individual or even as an organization. However

due to the global market and international presence of many companies

there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space

time and organizational boundaries via information and communication technologies. A global virtual team relies on communication

collaboration

and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study

we investigated factors that affect global virtual teams’ performance

factors considered include cultural differences

language problems

time-zone differences

team size

technical problems

lack of trust

lack of sufficient training

and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand

Ali Yahya Gheni

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