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Generalized Exponential Distribution :parameter Estimation and Means Comparison

Author: CuiJianGuo
Tutor: ShiJianHong
School: Shanxi Normal University
Course: Applied Mathematics
Keywords: Generalized exponential distribution q-Symmetric Entropy Loss Function modified maximum likelihood function zero failiurecdata Generalized p-value comparison of means admissibility
CLC: O211.3
Type: Master's thesis
Year: 2010
Downloads: 63
Quote: 0
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Recently the Generalized Exponential Distribution is a Lifetime Distribution by the authors Gupta and Kundu.It has a unimodel and right skewed density function, and increasing or de-creasing hazard rate depending on the shap parameter.It was observed that the two-parameter generalized exponential distribution could be used quite effectively to analyze positive lifetime data and kurtosis data,particularly,in place of the two-parameter gamma or two-parameter Weibull distribution.The main discussion about estimation of parameter and comparison of means for Generalized Exponential Distribution in this paper.In chapter two, we study the problem of Bayes estimation of parameter a when Generalized Exponential Distribution caused the q-Symmetric Entropy Loss distribution and under the three kinds of dissmilarity assumptions of priors,then give the discussion of admissibility.In chapter three, we study an approximate modified MLE of scaled parameter for the Gen-eralized Exponential Distribution under Zero Eailiure Data. First we obtain Bayes estimation of the accumulation failiure numbers Li of the modified maximum likelihood function by Bayes comprehensive assurance the method, meanwhile, approximately estimated of the scale param-eter for the Generalized Exponential Distribution will be gived by the function transformation abd Taler presumably series method.In chapter four, we discuss the problem of the comparison of means from the two Generalized Exponential Distributions of the same scale parameter, firstly of all,the comparison of means will be transformed to the comparison of the shap parameter the two Generalized Exponential Distribution using transformation thinking,finally, and obtain the generalized p-value.

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CLC: > Mathematical sciences and chemical > Mathematics > Probability Theory and Mathematical Statistics > Theory of probability ( probability theory, probability theory ) > Distribution theory
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