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Guided simulation of conditioned chemical reaction networks

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arxiv 2312.04457 v3 pith:YLSDJBPP submitted 2023-12-07 math.PR stat.CO

classification math.PRstat.CO
keywords processconditionedchemicaldotsgivenreactionresultsalgorithm
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abstract

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.

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Cited by 1 Pith paper

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  1. Backward Filtering Forward Guiding

    stat.ME 2025-05 conditional novelty 6.0 of 10

    A unified backward-filtering and forward-guiding scheme provides weighted posterior samples for latent processes on trees and DAGs with intractable transition densities.

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