| Knüsel, L. (2003): Alternatives to the MCMC method. Collaborative Research Center 386, Discussion Paper 367 |
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492Kb |
Abstract
The Markov Chain Monte Carlo method (MCMC) is often used to generate independent (pseudo) random numbers from a distribution with a density that is known only up to a normalising constant. With the MCMC method it is not necessary to compute the normalising constant (see e.g. Tierney, 1994; Besag, 2000). In this paper we show that the well-known acceptance-rejection algorithm also works with unnormalised densities, and so this algorithm can be used to confirm the results of the MCMC method in simple cases. We present an example with real data.
| Item Type: | Paper (Research Paper) |
|---|---|
| Collections: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
| Subjects: | 500 Science > 510 Mathematics |
| URN: | urn:nbn:de:bvb:19-epub-1742-6 |
| ID Code: | 1742 |
| Deposited On: | 10. Apr 2007 |
| Last Modified: | 08. Jan 2013 15:56 |
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