Bayesian inference on finite mixtures of exponential distributions
Dissertant
Thesis advisor
University
Islamic University
Faculty
Faculty of Science
Department
Department of Mathematics
University Country
Palestine (Gaza Strip)
Degree
Master
Degree Date
2016
English Abstract
Mixed distributions are widely used to model data in which each observation is assumed to come from one of a number of di erent groups.
In this thesis, we investigate the Bayesian estimation for the nite exponential mixture model using the Gibbs sampler as an important one of the MCMC methods.
Our approach in this thesis depends on using the Gibbs sampler to simulate a Markov chain which has the posterior density as its long-run (stationary) distribution.
Then we use the resulting sample to make the suitable Bayesian computations and draw conclusion about the unknown parameters of the exponential mixture model.
We conclude this thesis by presenting a real data example to illustrates our methodology.
Main Subjects
No. of Pages
89
Table of Contents
Table of contents.
Abstract.
Introduction.
Chapter One : Introduction to bayesian statistics.
Chapter Two : Finite mixtures of distributions.
Chapter Three : MCMC methods in bayesian Inference.
Chapter Four : Bayesian analysis of finite exponential mixtures.
References.
American Psychological Association (APA)
Salih, Ahlam M.. (2016). Bayesian inference on finite mixtures of exponential distributions. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-724332
Modern Language Association (MLA)
Salih, Ahlam M.. Bayesian inference on finite mixtures of exponential distributions. (Master's theses Theses and Dissertations Master). Islamic University. (2016).
https://search.emarefa.net/detail/BIM-724332
American Medical Association (AMA)
Salih, Ahlam M.. (2016). Bayesian inference on finite mixtures of exponential distributions. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-724332
Language
English
Data Type
Arab Theses
Record ID
BIM-724332
