{"title":"不规则SDEs的泛函极限定理","authors":"S. Ankirchner, T. Kruse, M. Urusov","doi":"10.1214/16-AIHP760","DOIUrl":null,"url":null,"abstract":"Let $X_1, X_2, \\ldots$ be a sequence of i.i.d. real-valued random variables with mean zero, and consider the scaled random walk of the form $Y^N_{k+1} = Y^N_{k} + a_N(Y^N_k) X_{k+1}$, where $a_N: \\mathbb R \\to \\mathbb R_+$. We show, under mild assumptions on the law of $X_i$, that one can choose the scale factor $a_N$ in such a way that the process $(Y^N_{\\lfloor N t \\rfloor})_{t \\in \\mathbb R_+}$ converges in distribution to a given diffusion $(M_t)_{t \\in \\mathbb R_+}$ solving a stochastic differential equation with possibly irregular coefficients, as $N \\to \\infty$. To this end we embed the scaled random walks into the diffusion $M$ with a sequence of stopping times with expected time step $1/N$.","PeriodicalId":7902,"journal":{"name":"Annales De L Institut Henri Poincare-probabilites Et Statistiques","volume":"9 1","pages":"1438-1457"},"PeriodicalIF":1.2000,"publicationDate":"2014-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A functional limit theorem for irregular SDEs\",\"authors\":\"S. Ankirchner, T. Kruse, M. Urusov\",\"doi\":\"10.1214/16-AIHP760\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Let $X_1, X_2, \\\\ldots$ be a sequence of i.i.d. real-valued random variables with mean zero, and consider the scaled random walk of the form $Y^N_{k+1} = Y^N_{k} + a_N(Y^N_k) X_{k+1}$, where $a_N: \\\\mathbb R \\\\to \\\\mathbb R_+$. We show, under mild assumptions on the law of $X_i$, that one can choose the scale factor $a_N$ in such a way that the process $(Y^N_{\\\\lfloor N t \\\\rfloor})_{t \\\\in \\\\mathbb R_+}$ converges in distribution to a given diffusion $(M_t)_{t \\\\in \\\\mathbb R_+}$ solving a stochastic differential equation with possibly irregular coefficients, as $N \\\\to \\\\infty$. To this end we embed the scaled random walks into the diffusion $M$ with a sequence of stopping times with expected time step $1/N$.\",\"PeriodicalId\":7902,\"journal\":{\"name\":\"Annales De L Institut Henri Poincare-probabilites Et Statistiques\",\"volume\":\"9 1\",\"pages\":\"1438-1457\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2014-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annales De L Institut Henri Poincare-probabilites Et Statistiques\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1214/16-AIHP760\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annales De L Institut Henri Poincare-probabilites Et Statistiques","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1214/16-AIHP760","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 7
摘要
设$X_1, X_2, \ldots$为均值为零的i.i.d实值随机变量序列,并考虑形式为$Y^N_{k+1} = Y^N_{k} + a_N(Y^N_k) X_{k+1}$的缩放随机游走,其中$a_N: \mathbb R \to \mathbb R_+$。我们表明,在对$X_i$定律的温和假设下,我们可以这样选择尺度因子$a_N$,使过程$(Y^N_{\lfloor N t \rfloor})_{t \in \mathbb R_+}$在分布上收敛于给定的扩散$(M_t)_{t \in \mathbb R_+}$,求解一个可能具有不规则系数的随机微分方程,如$N \to \infty$。为此,我们将缩放的随机漫步嵌入到扩散中$M$,并具有期望时间步长$1/N$的停止时间序列。
Let $X_1, X_2, \ldots$ be a sequence of i.i.d. real-valued random variables with mean zero, and consider the scaled random walk of the form $Y^N_{k+1} = Y^N_{k} + a_N(Y^N_k) X_{k+1}$, where $a_N: \mathbb R \to \mathbb R_+$. We show, under mild assumptions on the law of $X_i$, that one can choose the scale factor $a_N$ in such a way that the process $(Y^N_{\lfloor N t \rfloor})_{t \in \mathbb R_+}$ converges in distribution to a given diffusion $(M_t)_{t \in \mathbb R_+}$ solving a stochastic differential equation with possibly irregular coefficients, as $N \to \infty$. To this end we embed the scaled random walks into the diffusion $M$ with a sequence of stopping times with expected time step $1/N$.
期刊介绍:
The Probability and Statistics section of the Annales de l’Institut Henri Poincaré is an international journal which publishes high quality research papers. The journal deals with all aspects of modern probability theory and mathematical statistics, as well as with their applications.