• norsk
    • English
  • English 
    • norsk
    • English
  • Login
View Item 
  •   Home
  • Faculty of Mathematics and Natural Sciences
  • Department of Informatics
  • Department of Informatics
  • View Item
  •   Home
  • Faculty of Mathematics and Natural Sciences
  • Department of Informatics
  • Department of Informatics
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Improving Efficiency in Parameter Estimation Using the Hamiltonian Monte Carlo Algorithm

Alfaki, Mohammed
Master thesis
Thumbnail
View/Open
47444077.pdf (1.386Mb)
URI
https://hdl.handle.net/1956/3202
Date
2008
Metadata
Show full item record
Collections
  • Department of Informatics [740]
Abstract
This thesis investigates three approaches to improve the performance of the Hamiltonian Monte Carlo algorithm. The first approach enhances the Hamiltonian Monte Carlo by suppressing random walk in the Gibbs sampling using ordered over--relaxation. The second approach investigates the simulation of the Hamiltonian dynamics using an adaptive step--size to reduce the error of the simulation. The third proposal is to combine the two versions into one algorithm.
Publisher
The University of Bergen
Copyright
The author
Copyright the author. All rights reserved

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit
 

 

Browse

ArchiveCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDocument TypesJournalsThis CollectionBy Issue DateAuthorsTitlesSubjectsDocument TypesJournals

My Account

Login

Statistics

View Usage Statistics

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit