• norsk
    • English
  • English 
    • norsk
    • English
  • Login
View Item 
  •   Home
  • Fakultet for informasjonsteknologi og elektroteknikk (IE)
  • Institutt for matematiske fag
  • View Item
  •   Home
  • Fakultet for informasjonsteknologi og elektroteknikk (IE)
  • Institutt for matematiske fag
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

An Introduction to Approximate Bayesian Computation

Arthur Benjamin Osei
Master thesis
Thumbnail
View/Open
no.ntnu:inspera:35875848:23866786.pdf (620.8Kb)
URI
http://hdl.handle.net/11250/2613395
Date
2019
Metadata
Show full item record
Collections
  • Institutt for matematiske fag [1390]
Abstract
 
 
Approximate Bayesian Computation (ABC) methods is a technique usedto make parameter inference and model selection of issues of intractablelikelihood and complex models.In this thesis, we briefly discuss the philosophy of Bayesian inference andelaborated more on the definition, implementation and demonstration ofthe three ABC algorithms. We wanted to know the efficiency of the ABCmethods in computing the samples of posterior parameters compare to theanalytically computation of the posterior parameters. The ABC algorithmis applied on two simple toy examples. In these toy examples, the posteriorpdf is known before implementing the algorithm. We further compare thesamples of posterior parameter values obtained using ABC to the true pos-terior and hence verify the accuracy of the algorithm.
 
Publisher
NTNU

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