{"title":"时间稳定随机过程的级数表示","authors":"Christoph Kopp, I. Molchanov","doi":"10.19195/0208-4147.38.2.4","DOIUrl":null,"url":null,"abstract":"A stochastically continuous process ξt, t≥0, is said to be time-stable if the sum of n i.i.d. copies of ξ equals in distribution the time-scaled stochastic process ξnt, t≥0. The paper advances the understanding of time-stable processes by means of their LePage series representations as the sum of i.i.d. processes with the arguments scaled by the sequence of successive points of the unit intensity Poisson process on [0;∞. These series yield numerous examples of stochastic processes that share one-dimensional distributions with a Lévy process.","PeriodicalId":48996,"journal":{"name":"Probability and Mathematical Statistics-Poland","volume":"1 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2015-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Series representation of time-stable stochastic processes\",\"authors\":\"Christoph Kopp, I. Molchanov\",\"doi\":\"10.19195/0208-4147.38.2.4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A stochastically continuous process ξt, t≥0, is said to be time-stable if the sum of n i.i.d. copies of ξ equals in distribution the time-scaled stochastic process ξnt, t≥0. The paper advances the understanding of time-stable processes by means of their LePage series representations as the sum of i.i.d. processes with the arguments scaled by the sequence of successive points of the unit intensity Poisson process on [0;∞. These series yield numerous examples of stochastic processes that share one-dimensional distributions with a Lévy process.\",\"PeriodicalId\":48996,\"journal\":{\"name\":\"Probability and Mathematical Statistics-Poland\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2015-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Probability and Mathematical Statistics-Poland\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.19195/0208-4147.38.2.4\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Probability and Mathematical Statistics-Poland","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.19195/0208-4147.38.2.4","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: 8
摘要
随机连续过程ξt, t≥-0,如果ξ的n i id个副本的和在时间尺度随机过程ξnt, t≥0的分布上相等,则称为时间稳定过程。本文通过将时间稳定过程的LePage级数表示为i.i.d过程的和,其参数由单位强度泊松过程在[0;∞上的连续点的序列缩放,提出了时间稳定过程的理解。这些序列产生了许多与lsamvy过程共享一维分布的随机过程的例子。
Series representation of time-stable stochastic processes
A stochastically continuous process ξt, t≥0, is said to be time-stable if the sum of n i.i.d. copies of ξ equals in distribution the time-scaled stochastic process ξnt, t≥0. The paper advances the understanding of time-stable processes by means of their LePage series representations as the sum of i.i.d. processes with the arguments scaled by the sequence of successive points of the unit intensity Poisson process on [0;∞. These series yield numerous examples of stochastic processes that share one-dimensional distributions with a Lévy process.
期刊介绍:
PROBABILITY AND MATHEMATICAL STATISTICS is published by the Kazimierz Urbanik Center for Probability and Mathematical Statistics, and is sponsored jointly by the Faculty of Mathematics and Computer Science of University of Wrocław and the Faculty of Pure and Applied Mathematics of Wrocław University of Science and Technology. The purpose of the journal is to publish original contributions to the theory of probability and mathematical statistics.