{"title":"时域操作下R/S统计实现的行为","authors":"J. Pacheco","doi":"10.1109/ICEEE.2006.251935","DOIUrl":null,"url":null,"abstract":"Complex correlation structure of current communications network traffic requires the use of algorithms for detecting the degree of dependence in a sample path of the network traffic process. Several algorithms for accomplishing the above exists with varying degrees of accuracy and convergence. In this paper we study the R/S statistic, in particular, the accuracy, convergence and its effectiveness under time aggregation for several long-memory characteristics (fGn and FARIMA). We present the selection of the optimal values of the low and high-ends in the linear fit for three implementations of the R/S statistic. Based on the above we show that different implementations give varying degrees of accuracy, convergence and effectiveness under time aggregation","PeriodicalId":125310,"journal":{"name":"2006 3rd International Conference on Electrical and Electronics Engineering","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Behavior of R/S Statistic Implementations under Time-Domain Operations\",\"authors\":\"J. Pacheco\",\"doi\":\"10.1109/ICEEE.2006.251935\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Complex correlation structure of current communications network traffic requires the use of algorithms for detecting the degree of dependence in a sample path of the network traffic process. Several algorithms for accomplishing the above exists with varying degrees of accuracy and convergence. In this paper we study the R/S statistic, in particular, the accuracy, convergence and its effectiveness under time aggregation for several long-memory characteristics (fGn and FARIMA). We present the selection of the optimal values of the low and high-ends in the linear fit for three implementations of the R/S statistic. Based on the above we show that different implementations give varying degrees of accuracy, convergence and effectiveness under time aggregation\",\"PeriodicalId\":125310,\"journal\":{\"name\":\"2006 3rd International Conference on Electrical and Electronics Engineering\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 3rd International Conference on Electrical and Electronics Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEEE.2006.251935\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 3rd International Conference on Electrical and Electronics Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEE.2006.251935","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Behavior of R/S Statistic Implementations under Time-Domain Operations
Complex correlation structure of current communications network traffic requires the use of algorithms for detecting the degree of dependence in a sample path of the network traffic process. Several algorithms for accomplishing the above exists with varying degrees of accuracy and convergence. In this paper we study the R/S statistic, in particular, the accuracy, convergence and its effectiveness under time aggregation for several long-memory characteristics (fGn and FARIMA). We present the selection of the optimal values of the low and high-ends in the linear fit for three implementations of the R/S statistic. Based on the above we show that different implementations give varying degrees of accuracy, convergence and effectiveness under time aggregation