Saved in:
| Main Author: | |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.13182 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916295221444608 |
|---|---|
| author | Goodman, Jesse |
| author_facet | Goodman, Jesse |
| contents | This paper presents an identity between the multivariate and univariate saddlepoint approximations applied to sample path probabilities for a certain class of stochastic processes. This class, which we term the recursively compounded processes, includes branching processes and other models featuring sums of a random number of i.i.d. terms; and compound Poisson processes and other Lévy processes in which the additive parameter is itself chosen randomly. For such processes, $\hat{f}_{X_1,\dotsc,X_N | X_0=x_0}(x_1,\dots,x_N) = \prod_{n=1}^N \hat{f}_{X_n | X_0=x_0,\dots,X_{n-1}=x_{n-1}}(x_n),$ where the left-hand side is a multivariate saddlepoint approximation applied to the random vector $(X_1,\dots,X_N)$ and the right-hand side is a product of univariate saddlepoint approximations applied to the conditional one-step distributions given the past. Two proofs are given. The first proof is analytic, based on a change-of-variables identity linking the functions that arise in the respective saddlepoint approximations. The second proof is probabilistic, based on a representation of the saddlepoint approximation in terms of tilted distributions, changes of measure, and relative entropies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_13182 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The saddlepoint approximation factors over sample paths of recursively compounded processes Goodman, Jesse Probability 60E10, 41A60 (Primary) 60J80 (Secondary) This paper presents an identity between the multivariate and univariate saddlepoint approximations applied to sample path probabilities for a certain class of stochastic processes. This class, which we term the recursively compounded processes, includes branching processes and other models featuring sums of a random number of i.i.d. terms; and compound Poisson processes and other Lévy processes in which the additive parameter is itself chosen randomly. For such processes, $\hat{f}_{X_1,\dotsc,X_N | X_0=x_0}(x_1,\dots,x_N) = \prod_{n=1}^N \hat{f}_{X_n | X_0=x_0,\dots,X_{n-1}=x_{n-1}}(x_n),$ where the left-hand side is a multivariate saddlepoint approximation applied to the random vector $(X_1,\dots,X_N)$ and the right-hand side is a product of univariate saddlepoint approximations applied to the conditional one-step distributions given the past. Two proofs are given. The first proof is analytic, based on a change-of-variables identity linking the functions that arise in the respective saddlepoint approximations. The second proof is probabilistic, based on a representation of the saddlepoint approximation in terms of tilted distributions, changes of measure, and relative entropies. |
| title | The saddlepoint approximation factors over sample paths of recursively compounded processes |
| topic | Probability 60E10, 41A60 (Primary) 60J80 (Secondary) |
| url | https://arxiv.org/abs/2406.13182 |