Vyshemirsky, Vladislav (2012) Evidential model ranking without likelihoods. In: MASAMB, 2012-04-10 - 2012-04-11, Berlin.
Full text not available in this repository. (Request a copy from the Strathclyde author)Abstract
We present a probabilistic formulation of the Approximate Bayesian Computation scheme that allows evidential ranking of alternative models without direct use of a likelihood function. This approach is particularly important when ranking of several sophisticated stochastic models is desired, and the likelihood is either too complex or impossible to define. We suggest a modification of a Sequential Monte-Carlo sampler that uses ideas of Path Sampling to estimate an approximation to marginal likelihoods as a measure of evidence support. We demonstrate applications of this method on a problem of ranking alternative models of cancerous tumour growth using unique data from three cancerous spheroid lines.
| Item type: | Conference or Workshop Item (Speech) |
|---|---|
| ID code: | 41461 |
| Keywords: | Approximate Bayesian Computation , probability, Path Sampling, Probabilities. Mathematical statistics |
| Subjects: | Science > Mathematics > Probabilities. Mathematical statistics |
| Department: | Faculty of Science > Mathematics and Statistics |
| Related URLs: | |
| Depositing user: | Pure Administrator |
| Date Deposited: | 15 Oct 2012 15:00 |
| Last modified: | 15 Oct 2012 15:00 |
| URI: | http://strathprints.strath.ac.uk/id/eprint/41461 |
Actions (login required)
| View Item |