{"title":"一种新的具有长期相关性的随机过程","authors":"Sung Ik Kim, Y. S. Kim","doi":"10.2991/jsta.d.200923.001","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a fractional Generalized Hyperbolic process, a new stochastic process with long-range dependence obtained by subordinating fractional Brownianmotion to a fractionalGeneralized InverseGaussian process. The basic properties and covariance structure between the elements of the processes are discussed, and we present numerical methods to generate the sample paths for the processes.","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Stochastic Process with Long-Range Dependence\",\"authors\":\"Sung Ik Kim, Y. S. Kim\",\"doi\":\"10.2991/jsta.d.200923.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce a fractional Generalized Hyperbolic process, a new stochastic process with long-range dependence obtained by subordinating fractional Brownianmotion to a fractionalGeneralized InverseGaussian process. The basic properties and covariance structure between the elements of the processes are discussed, and we present numerical methods to generate the sample paths for the processes.\",\"PeriodicalId\":45080,\"journal\":{\"name\":\"Journal of Statistical Theory and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistical Theory and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/jsta.d.200923.001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/jsta.d.200923.001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
A New Stochastic Process with Long-Range Dependence
In this paper, we introduce a fractional Generalized Hyperbolic process, a new stochastic process with long-range dependence obtained by subordinating fractional Brownianmotion to a fractionalGeneralized InverseGaussian process. The basic properties and covariance structure between the elements of the processes are discussed, and we present numerical methods to generate the sample paths for the processes.
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