The Library
Likelihood-free inference via classification
Tools
Tools
Tools
Gutmann, Michael U., Dutta, Ritabrata, Kaski, Samuel and Corander, Jukka (2018) Likelihood-free inference via classification. Statistics and Computing, 28 (2). pp. 411-425. doi:10.1007/s11222-017-9738-6 ISSN 0960-3174.
Research output not available from this repository.
Request-a-Copy directly from author or use local Library Get it For Me service.
Official URL: http://dx.doi.org/10.1007/s11222-017-9738-6
Abstract
Increasingly complex generative models are being used across disciplines as they allow for realistic characterization of data, but a common difficulty with them is the prohibitively large computational cost to evaluate the likelihood function and thus to perform likelihood-based statistical inference. A likelihood-free inference framework has emerged where the parameters are identified by finding values that yield simulated data resembling the observed data. While widely applicable, a major difficulty in this framework is how to measure the discrepancy between the simulated and observed data. Transforming the original problem into a problem of classifying the data into simulated versus observed, we find that classification accuracy can be used to assess the discrepancy. The complete arsenal of classification methods becomes thereby available for inference of intractable generative models. We validate our approach using theory and simulations for both point estimation and Bayesian inference, and demonstrate its use on real data by inferring an individual-based epidemiological model for bacterial infections in child care centers.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||
| Journal or Publication Title: | Statistics and Computing | ||||||||
| Publisher: | Springer | ||||||||
| ISSN: | 0960-3174 | ||||||||
| Official Date: | March 2018 | ||||||||
| Dates: |
|
||||||||
| Volume: | 28 | ||||||||
| Number: | 2 | ||||||||
| Page Range: | pp. 411-425 | ||||||||
| DOI: | 10.1007/s11222-017-9738-6 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access (Creative Commons) |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
