Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.11233 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866911379981598720 |
|---|---|
| author | Alquier, Pierre Fermanian, Jean-David Poignard, Benjamin |
| author_facet | Alquier, Pierre Fermanian, Jean-David Poignard, Benjamin |
| contents | We define two minimum distance estimators for dependent data by minimizing some approximated Maximum Mean Discrepancy distances between the true empirical distribution of observations and their assumed (parametric) model distribution. When the latter one is intractable, it is approximated by simulation, allowing to accommodate most dynamic processes with latent variables. We derive the non-asymptotic and the large sample properties of our estimators in the context of absolutely regular/beta-mixing random elements. Our simulation experiments illustrate the robustness of our procedures to model misspecification, particularly in comparison with alternative standard estimation methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_11233 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Estimation of time series by Maximum Mean Discrepancy Alquier, Pierre Fermanian, Jean-David Poignard, Benjamin Methodology We define two minimum distance estimators for dependent data by minimizing some approximated Maximum Mean Discrepancy distances between the true empirical distribution of observations and their assumed (parametric) model distribution. When the latter one is intractable, it is approximated by simulation, allowing to accommodate most dynamic processes with latent variables. We derive the non-asymptotic and the large sample properties of our estimators in the context of absolutely regular/beta-mixing random elements. Our simulation experiments illustrate the robustness of our procedures to model misspecification, particularly in comparison with alternative standard estimation methods. |
| title | Estimation of time series by Maximum Mean Discrepancy |
| topic | Methodology |
| url | https://arxiv.org/abs/2601.11233 |