Strong approximation and central limit theorems for multiscale stochastic gene networks
Fuente:
arXiv
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866917304007131136 |
|---|---|
| author | Huguet, Baptiste Nicolas |
| author_facet | Huguet, Baptiste Nicolas |
| contents | We study a mutliscale jump process introduced in a work by Crudu, Debussche, Muller and Radulescu. Using an adequate coupling, we are able to prove the strong convergence, for the uniform topology, to a piecewise deterministic Markov process. Under some additional regularity, we also obtain a central limit theorem and prove that the fluctuations of the continuous scale converge, in a weaker sense, to the solution of a stochastic differential equation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_04768 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Strong approximation and central limit theorems for multiscale stochastic gene networks Huguet, Baptiste Nicolas Probability We study a mutliscale jump process introduced in a work by Crudu, Debussche, Muller and Radulescu. Using an adequate coupling, we are able to prove the strong convergence, for the uniform topology, to a piecewise deterministic Markov process. Under some additional regularity, we also obtain a central limit theorem and prove that the fluctuations of the continuous scale converge, in a weaker sense, to the solution of a stochastic differential equation. |
| title | Strong approximation and central limit theorems for multiscale stochastic gene networks |
| topic | Probability |
| url | https://arxiv.org/abs/2504.04768 |