Using MCMC methods in some application problems

Parvin Azhdari; Nader Jafarpanahi; Arman Beitollahi

doi:10.14419/ijsw.v2i2.2967

Article Details

Using MCMC methods in some application problems

Authors:

Parvin Azhdari | Nader Jafarpanahi | Arman Beitollahi

Publisher:

Science Publishing Corporation

Journal:

International Journal of Scientific World Vol.2 Issue 2, pp.48-55

Document Type:

Article

Publication Date:

7/2014

Document Language:

English

Document ID (Org No.):

2001388255

pISSN:

2307-9037

DOI:

10.14419/ijsw.v2i2.2967

Abstract:

 MCMC methods are very important tools for estimating unknown parameters in Bayesian models. Especially in the case of high dimensions. Gaussian mixture model is one of the applications of estimating hyper parameters by MCMC method. Keywords: Gibbs Sampling, Slice Sampling, Metropolis-Hastings Algorithm, Gaussian, Mixture Model.

Article Details

Using MCMC methods in some application problems

Authors: Parvin Azhdari | Nader Jafarpanahi | Arman Beitollahi

Publisher: Science Publishing Corporation

Journal: International Journal of Scientific World Vol.2 Issue 2, pp.48-55

Document Type: Article

Publication Date: 7/2014

Document Language: English

Document ID (Org No.): 2001388255

pISSN: 2307-9037

DOI: 10.14419/ijsw.v2i2.2967

Issues

Authors:

Parvin Azhdari | Nader Jafarpanahi | Arman Beitollahi

Publisher:

Science Publishing Corporation

Journal:

International Journal of Scientific World Vol.2 Issue 2, pp.48-55

Document Type:

Article

Publication Date:

7/2014

Document Language:

English

Document ID (Org No.):

2001388255

pISSN:

2307-9037

DOI:

10.14419/ijsw.v2i2.2967