Journal article
Grapham: Graphical models with adaptive random walk Metropolis algorithms
- Abstract:
-
Recently developed adaptive Markov chain Monte Carlo (MCMC) methods have been applied successfully to many problems in Bayesian statistics. Grapham is a new open source implementation covering several such methods, with emphasis on graphical models for directed acyclic graphs. The implemented algorithms include the seminal Adaptive Metropolis algorithm adjusting the proposal covariance according to the history of the chain and a Metropolis algorithm adjusting the proposal scale based on the o...
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- Publisher copy:
- 10.1016/j.csda.2009.09.001
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Bibliographic Details
- Journal:
- Computational Statistics and Data Analysis
- Volume:
- 54
- Issue:
- 1
- Pages:
- 49-54
- Publication date:
- 2010-01-01
- DOI:
- ISSN:
-
0167-9473
- Source identifiers:
-
487896
Item Description
- Language:
- English
- Pubs id:
-
pubs:487896
- UUID:
-
uuid:14d3a883-09cd-4f1d-9f5e-01b950010f00
- Local pid:
- pubs:487896
- Deposit date:
- 2014-11-11
Terms of use
- Copyright date:
- 2010
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