Markov chain Monte Carlo method and perfect simulation
Dissertant
Thesis advisor
University
Islamic University
Faculty
Faculty of Science
Department
Department of Mathematics
University Country
Palestine (Gaza Strip)
Degree
Master
Degree Date
2007
English Abstract
Markov Chain Monte Carlo method is used to sample from complicated multivariate distribution with normalizing constants that may not be computable and from which direct sampling is not feasible.
Recent years have seen the development of a new, exciting generation of Markov Chain Monte Carlo method: perfect simulation algorithms. In this thesis, we give a review of the new perfect simulation algorithms using Markov chains, focused on the method called Coupling From The Past, since it allows not only an approximate but perfect (exact) simulation of the stationary distribution of ¯note state space Markov chain.
Main Subjects
Topics
No. of Pages
76
Table of Contents
Contents.
Abstract.
Chapter 1 : Markov chains.
Chapter 2 : Markov chain monte carlo algorithms.
Chapter 3 : Coupling.
Chapter 4 : Perfect simulation.
American Psychological Association (APA)
Karam, Arwah Numan. (2007). Markov chain Monte Carlo method and perfect simulation. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-299328
Modern Language Association (MLA)
Karam, Arwah Numan. Markov chain Monte Carlo method and perfect simulation. (Master's theses Theses and Dissertations Master). Islamic University. (2007).
https://search.emarefa.net/detail/BIM-299328
American Medical Association (AMA)
Karam, Arwah Numan. (2007). Markov chain Monte Carlo method and perfect simulation. (Master's theses Theses and Dissertations Master). Islamic University, Palestine (Gaza Strip)
https://search.emarefa.net/detail/BIM-299328
Language
English
Data Type
Arab Theses
Record ID
BIM-299328
