The Library
On parameter estimation with the Wasserstein distance
Tools
Tools
Tools
Bernton, Espen, Jacob, Pierre E., Gerber, Mathieu and Robert, Christian P. (2019) On parameter estimation with the Wasserstein distance. Information and Inference, 8 (4). pp. 657-676. doi:10.1093/imaiai/iaz003 ISSN 2049-8764.
|
PDF
WRAP-parameter-estimation-Wasserstein-distance-Robert-2019.pdf - Accepted Version - Requires a PDF viewer. Download (4Mb) | Preview |
Official URL: https://doi.org/10.1093/imaiai/iaz003
Abstract
Statistical inference can be performed by minimizing, over the parameter space, the Wasserstein distance between model distributions and the empirical distribution of the data. We study asymptotic properties of such minimum Wasserstein distance estimators, complementing results derived by Bassetti, Bodini and Regazzini in 2006. In particular, our results cover the misspecified setting, in which the data-generating process is not assumed to be part of the family of distributions described by the model. Our results are motivated by recent applications of minimum Wasserstein estimators to complex generative models. We discuss some difficulties arising in the numerical approximation of these estimators. Two of our numerical examples (g-and-κ and sum of log-normals) are taken from the literature on approximate Bayesian computation and have likelihood functions that are not analytically tractable. Two other examples involve misspecified models.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics | ||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Mathematics Faculty of Science, Engineering and Medicine > Science > Statistics |
||||||||
| Library of Congress Subject Headings (LCSH): | Estimation theory, Mathematical statistics | ||||||||
| Journal or Publication Title: | Information and Inference | ||||||||
| Publisher: | Oxford University Press | ||||||||
| ISSN: | 2049-8764 | ||||||||
| Official Date: | December 2019 | ||||||||
| Dates: |
|
||||||||
| Volume: | 8 | ||||||||
| Number: | 4 | ||||||||
| Page Range: | pp. 657-676 | ||||||||
| DOI: | 10.1093/imaiai/iaz003 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Reuse Statement (publisher, data, author rights): | This is a pre-copyedited, author-produced version of an article accepted for publication in Information and Inference following peer review. The version of record 22/10/2019 is available online at: https://doi.org/10.1093/imaiai/iaz003 | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Date of first compliant deposit: | 25 March 2019 | ||||||||
| Date of first compliant Open Access: | 22 October 2020 | ||||||||
| RIOXX Funder/Project Grant: |
|
||||||||
| Related URLs: | |||||||||
| Open Access Version: |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
