Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.11167 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917382961758208 |
|---|---|
| author | Li, Si-Yang van Dyk, David A. Autenrieth, Maximilian |
| author_facet | Li, Si-Yang van Dyk, David A. Autenrieth, Maximilian |
| contents | This paper presents a novel method for analytical derivations of marginal densities using the fractional derivatives of moment-generating functions. Although the method requires likelihood functions to take specific forms, its assumptions are otherwise modest. It only requires that the prior moment-generating functions exist, are finite, and are continuous and differentiable at certain points. We also present the probabilistic and statistical insights behind this method. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_11167 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Using fractional derivatives to derive marginal densities Li, Si-Yang van Dyk, David A. Autenrieth, Maximilian Methodology Statistics Theory This paper presents a novel method for analytical derivations of marginal densities using the fractional derivatives of moment-generating functions. Although the method requires likelihood functions to take specific forms, its assumptions are otherwise modest. It only requires that the prior moment-generating functions exist, are finite, and are continuous and differentiable at certain points. We also present the probabilistic and statistical insights behind this method. |
| title | Using fractional derivatives to derive marginal densities |
| topic | Methodology Statistics Theory |
| url | https://arxiv.org/abs/2409.11167 |