Exponential Family Trend Filtering on Lattices
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2022
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866909451791892480 |
|---|---|
| author | Sadhanala, Veeranjaneyulu Bassett, Robert Sharpnack, James McDonald, Daniel J. |
| author_facet | Sadhanala, Veeranjaneyulu Bassett, Robert Sharpnack, James McDonald, Daniel J. |
| contents | Trend filtering is a modern approach to nonparametric regression that is more adaptive to local smoothness than splines or similar basis procedures. Existing analyses of trend filtering focus on estimating a function corrupted by homoskedastic Gaussian noise, but our work extends this technique to general exponential family distributions. This extension is motivated by the need to study massive, gridded climate data derived from polar-orbiting satellites. We present algorithms tailored to large problems, theoretical results for general exponential family likelihoods, and principled methods for tuning parameter selection without excess computation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2209_09175 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Exponential Family Trend Filtering on Lattices Sadhanala, Veeranjaneyulu Bassett, Robert Sharpnack, James McDonald, Daniel J. Statistics Theory Trend filtering is a modern approach to nonparametric regression that is more adaptive to local smoothness than splines or similar basis procedures. Existing analyses of trend filtering focus on estimating a function corrupted by homoskedastic Gaussian noise, but our work extends this technique to general exponential family distributions. This extension is motivated by the need to study massive, gridded climate data derived from polar-orbiting satellites. We present algorithms tailored to large problems, theoretical results for general exponential family likelihoods, and principled methods for tuning parameter selection without excess computation. |
| title | Exponential Family Trend Filtering on Lattices |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2209.09175 |