What is the price of approximation? The saddlepoint approximation to a likelihood function
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866912319467945984 |
|---|---|
| author | Oketch, Godrick Fewster, Rachel M. Goodman, Jesse |
| author_facet | Oketch, Godrick Fewster, Rachel M. Goodman, Jesse |
| contents | The saddlepoint approximation to the likelihood, and its corresponding maximum likelihood estimate (MLE), offer an alternative estimation method when the true likelihood is intractable or computationally expensive. However, maximizing this approximated likelihood instead of the true likelihood inevitably comes at a price: a discrepancy between the MLE derived from the saddlepoint approximation and the true MLE. In previous studies, the size of this discrepancy has been investigated via simulation, or by engaging with the true likelihood despite its computational difficulties. Here, we introduce an explicit and computable approximation formula for the discrepancy, through which the adequacy of the saddlepoint-based MLE can be directly assessed. We present examples demonstrating the accuracy of this formula in specific cases where the true likelihood can be calculated. Additionally, we present asymptotic results that capture the behaviour of the discrepancy in a suitable limiting framework. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_07324 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | What is the price of approximation? The saddlepoint approximation to a likelihood function Oketch, Godrick Fewster, Rachel M. Goodman, Jesse Methodology 62F10, 62F12 The saddlepoint approximation to the likelihood, and its corresponding maximum likelihood estimate (MLE), offer an alternative estimation method when the true likelihood is intractable or computationally expensive. However, maximizing this approximated likelihood instead of the true likelihood inevitably comes at a price: a discrepancy between the MLE derived from the saddlepoint approximation and the true MLE. In previous studies, the size of this discrepancy has been investigated via simulation, or by engaging with the true likelihood despite its computational difficulties. Here, we introduce an explicit and computable approximation formula for the discrepancy, through which the adequacy of the saddlepoint-based MLE can be directly assessed. We present examples demonstrating the accuracy of this formula in specific cases where the true likelihood can be calculated. Additionally, we present asymptotic results that capture the behaviour of the discrepancy in a suitable limiting framework. |
| title | What is the price of approximation? The saddlepoint approximation to a likelihood function |
| topic | Methodology 62F10, 62F12 |
| url | https://arxiv.org/abs/2504.07324 |