Modelling and analysis of biomedical data using Markov chain Monte Carlo
The aim of this dissertation is to present the problem of biomedical model analysis using Markov Chain Monte Carlo (MCMC), and to provide pointers to the literature for further details. We also present a case study using the most basic of MCMC techniques, the Gibbs sampler.
Saved in:
Main Author: | Tao, Bo. |
---|---|
Other Authors: | Chin, Teck Chai |
Format: | Theses and Dissertations |
Published: |
2008
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/3412 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Similar Items
-
Accurate building occupancy estimation with inhomogeneous Markov chain
by: Lee, Jun Hao
Published: (2022) -
Super-resolution imaging : Markov chain Monte Carlo and state-space approaches
by: Tian, Jing
Published: (2011) -
Human pose estimation based on data-driven Monte Carlo hidden Markov models
by: Tao, Meng
Published: (2008) -
Classification and feature selection for biomedical and biological data using soft computing
by: Zhou, Nina
Published: (2011) -
Modeling protein structure alignment based on Markov random field theory
by: Sheng, Xin.
Published: (2008)