Statistical Inference for Stochastic Processes随机过程统计推断
Statistical Inference for Stochastic Processes(英文缩写 STAT INFER STOCH PRO),ISSN 1387-0874,eISSN 1572-9311,中文译名:随机过程统计推断 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-10-01 至 2026-09-30，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2020 | 未收录 | N/A |
| 2021 | 未收录 | N/A |
| 2022 | 0.800 | N/A |
| 2023 | 0.700 | Q3 |
| 2024 | 1.000 | Q3 |
Statistical Inference for Stochastic Processes 最新收录文献
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1. Adaptive exact recovery in sparse nonparametric models.
PMID:日期:2025-10-27We observe an unknown function of variables , , in the Gaussian white noise model of intensity . We assume that the function is regular and that it is a sum of -variate functions, where varies from 1 to ( ). These functions are unknown to us and only a few of them are nonzero. In this article, we address the problem of identifying the nonzero components of in the case when as and is either fixed or , as . This may be viewed as a variable selection problem. We derive the conditions when exact variable selection in the model at hand is possible and provide a selection procedure that achieves this type of selection. The procedure is adaptive to a degree of model sparsity described by the sparsity parameter . We also derive conditions that make the exact variable selection impossible. Our results augment previous work in this area.
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2. Guided simulation of conditioned chemical reaction networks.
PMID:日期:2025-05-17Let be a chemical reaction process, modeled as a multi-dimensional continuous-time jump process. Assume that at given times , linear combinations are observed for given matrices . We show how the process that is conditioned on hitting the states 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.