{"title":"Lipschitz映射迭代函数系统的鲁棒性","authors":"L. Hervé, J. Ledoux","doi":"10.1017/jpr.2022.107","DOIUrl":null,"url":null,"abstract":"Abstract Let \n$\\{X_n\\}_{n\\in{\\mathbb{N}}}$\n be an \n${\\mathbb{X}}$\n -valued iterated function system (IFS) of Lipschitz maps defined as \n$X_0 \\in {\\mathbb{X}}$\n and for \n$n\\geq 1$\n , \n$X_n\\;:\\!=\\;F(X_{n-1},\\vartheta_n)$\n , where \n$\\{\\vartheta_n\\}_{n \\ge 1}$\n are independent and identically distributed random variables with common probability distribution \n$\\mathfrak{p}$\n , \n$F(\\cdot,\\cdot)$\n is Lipschitz continuous in the first variable, and \n$X_0$\n is independent of \n$\\{\\vartheta_n\\}_{n \\ge 1}$\n . Under parametric perturbation of both F and \n$\\mathfrak{p}$\n , we are interested in the robustness of the V-geometrical ergodicity property of \n$\\{X_n\\}_{n\\in{\\mathbb{N}}}$\n , of its invariant probability measure, and finally of the probability distribution of \n$X_n$\n . Specifically, we propose a pattern of assumptions for studying such robustness properties for an IFS. This pattern is implemented for the autoregressive processes with autoregressive conditional heteroscedastic errors, and for IFS under roundoff error or under thresholding/truncation. Moreover, we provide a general set of assumptions covering the classical Feller-type hypotheses for an IFS to be a V-geometrical ergodic process. An accurate bound for the rate of convergence is also provided.","PeriodicalId":50256,"journal":{"name":"Journal of Applied Probability","volume":"60 1","pages":"921 - 944"},"PeriodicalIF":0.7000,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Robustness of iterated function systems of Lipschitz maps\",\"authors\":\"L. Hervé, J. Ledoux\",\"doi\":\"10.1017/jpr.2022.107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Let \\n$\\\\{X_n\\\\}_{n\\\\in{\\\\mathbb{N}}}$\\n be an \\n${\\\\mathbb{X}}$\\n -valued iterated function system (IFS) of Lipschitz maps defined as \\n$X_0 \\\\in {\\\\mathbb{X}}$\\n and for \\n$n\\\\geq 1$\\n , \\n$X_n\\\\;:\\\\!=\\\\;F(X_{n-1},\\\\vartheta_n)$\\n , where \\n$\\\\{\\\\vartheta_n\\\\}_{n \\\\ge 1}$\\n are independent and identically distributed random variables with common probability distribution \\n$\\\\mathfrak{p}$\\n , \\n$F(\\\\cdot,\\\\cdot)$\\n is Lipschitz continuous in the first variable, and \\n$X_0$\\n is independent of \\n$\\\\{\\\\vartheta_n\\\\}_{n \\\\ge 1}$\\n . Under parametric perturbation of both F and \\n$\\\\mathfrak{p}$\\n , we are interested in the robustness of the V-geometrical ergodicity property of \\n$\\\\{X_n\\\\}_{n\\\\in{\\\\mathbb{N}}}$\\n , of its invariant probability measure, and finally of the probability distribution of \\n$X_n$\\n . Specifically, we propose a pattern of assumptions for studying such robustness properties for an IFS. This pattern is implemented for the autoregressive processes with autoregressive conditional heteroscedastic errors, and for IFS under roundoff error or under thresholding/truncation. Moreover, we provide a general set of assumptions covering the classical Feller-type hypotheses for an IFS to be a V-geometrical ergodic process. An accurate bound for the rate of convergence is also provided.\",\"PeriodicalId\":50256,\"journal\":{\"name\":\"Journal of Applied Probability\",\"volume\":\"60 1\",\"pages\":\"921 - 944\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Probability\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1017/jpr.2022.107\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Probability","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1017/jpr.2022.107","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Robustness of iterated function systems of Lipschitz maps
Abstract Let
$\{X_n\}_{n\in{\mathbb{N}}}$
be an
${\mathbb{X}}$
-valued iterated function system (IFS) of Lipschitz maps defined as
$X_0 \in {\mathbb{X}}$
and for
$n\geq 1$
,
$X_n\;:\!=\;F(X_{n-1},\vartheta_n)$
, where
$\{\vartheta_n\}_{n \ge 1}$
are independent and identically distributed random variables with common probability distribution
$\mathfrak{p}$
,
$F(\cdot,\cdot)$
is Lipschitz continuous in the first variable, and
$X_0$
is independent of
$\{\vartheta_n\}_{n \ge 1}$
. Under parametric perturbation of both F and
$\mathfrak{p}$
, we are interested in the robustness of the V-geometrical ergodicity property of
$\{X_n\}_{n\in{\mathbb{N}}}$
, of its invariant probability measure, and finally of the probability distribution of
$X_n$
. Specifically, we propose a pattern of assumptions for studying such robustness properties for an IFS. This pattern is implemented for the autoregressive processes with autoregressive conditional heteroscedastic errors, and for IFS under roundoff error or under thresholding/truncation. Moreover, we provide a general set of assumptions covering the classical Feller-type hypotheses for an IFS to be a V-geometrical ergodic process. An accurate bound for the rate of convergence is also provided.
期刊介绍:
Journal of Applied Probability is the oldest journal devoted to the publication of research in the field of applied probability. It is an international journal published by the Applied Probability Trust, and it serves as a companion publication to the Advances in Applied Probability. Its wide audience includes leading researchers across the entire spectrum of applied probability, including biosciences applications, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used.
A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.