{"title":"Reduced processes evolving in a mixed environment","authors":"C. Smadi, V. Vatutin","doi":"10.1080/15326349.2021.2015386","DOIUrl":null,"url":null,"abstract":"Abstract We consider a two-type decomposable branching process where type 1 particles may produce particles of types 1 and 2 while type 2 particles can give birth only to type 2 particles. Let i = 1, 2 be the number of type i particles existing in the process at moment m < n and having a positive number of descendants at moment n. Assuming that particles of the first type evolve in a random environment and particles of the second type evolve in a constant environment we investigate the distribution of the random vector when and","PeriodicalId":21970,"journal":{"name":"Stochastic Models","volume":"39 1","pages":"5 - 20"},"PeriodicalIF":0.5000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stochastic Models","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/15326349.2021.2015386","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract We consider a two-type decomposable branching process where type 1 particles may produce particles of types 1 and 2 while type 2 particles can give birth only to type 2 particles. Let i = 1, 2 be the number of type i particles existing in the process at moment m < n and having a positive number of descendants at moment n. Assuming that particles of the first type evolve in a random environment and particles of the second type evolve in a constant environment we investigate the distribution of the random vector when and
期刊介绍:
Stochastic Models publishes papers discussing the theory and applications of probability as they arise in the modeling of phenomena in the natural sciences, social sciences and technology. It presents novel contributions to mathematical theory, using structural, analytical, algorithmic or experimental approaches. In an interdisciplinary context, it discusses practical applications of stochastic models to diverse areas such as biology, computer science, telecommunications modeling, inventories and dams, reliability, storage, queueing theory, mathematical finance and operations research.