Guided simulation of conditioned chemical reaction networks

Fuente: arXiv
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Main Authors: Corstanje, Marc, van der Meulen, Frank
Format: Preprint
Published: 2023
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author Corstanje, Marc
van der Meulen, Frank
author_facet Corstanje, Marc
van der Meulen, Frank
contents Let $X$ be a chemical reaction process, modeled as a multi-dimensional continuous-time jump process. Assume that at given times $0< t_1 < \cdots <t_n$, linear combinations $v_i = L_i X(t_i),\, i=1,\dots ,n$ are observed for given matrices $L_i$. We show how the process that is conditioned on hitting the states $v_1,\dots, v_n$ is obtained by a change of measure on the law of the unconditioned process. This results in an algorithm for obtaining weighted samples from the conditioned process. Our results are illustrated by numerical simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2312_04457
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Guided simulation of conditioned chemical reaction networks
Corstanje, Marc
van der Meulen, Frank
Probability
Computation
60J27, 60J28, 60J74
Let $X$ be a chemical reaction process, modeled as a multi-dimensional continuous-time jump process. Assume that at given times $0< t_1 < \cdots <t_n$, linear combinations $v_i = L_i X(t_i),\, i=1,\dots ,n$ are observed for given matrices $L_i$. We show how the process that is conditioned on hitting the states $v_1,\dots, v_n$ is obtained by a change of measure on the law of the unconditioned process. This results in an algorithm for obtaining weighted samples from the conditioned process. Our results are illustrated by numerical simulations.
title Guided simulation of conditioned chemical reaction networks
topic Probability
Computation
60J27, 60J28, 60J74
url https://arxiv.org/abs/2312.04457