{"title":"Fully lifted interpolating comparisons of bilinearly indexed random processes","authors":"Mihailo Stojnic","doi":"arxiv-2311.18092","DOIUrl":null,"url":null,"abstract":"A powerful statistical interpolating concept, which we call \\emph{fully\nlifted} (fl), is introduced and presented while establishing a connection\nbetween bilinearly indexed random processes and their corresponding fully\ndecoupled (linearly indexed) comparative alternatives. Despite on occasion very\ninvolved technical considerations, the final interpolating forms and their\nunderlying relations admit rather elegant expressions that provide conceivably\nhighly desirable and useful tool for further studying various different aspects\nof random processes and their applications. We also discuss the generality of\nthe considered models and show that they encompass many well known random\nstructures and optimization problems to which then the obtained results\nautomatically apply.","PeriodicalId":501330,"journal":{"name":"arXiv - MATH - Statistics Theory","volume":"91 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - MATH - Statistics Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2311.18092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A powerful statistical interpolating concept, which we call \emph{fully
lifted} (fl), is introduced and presented while establishing a connection
between bilinearly indexed random processes and their corresponding fully
decoupled (linearly indexed) comparative alternatives. Despite on occasion very
involved technical considerations, the final interpolating forms and their
underlying relations admit rather elegant expressions that provide conceivably
highly desirable and useful tool for further studying various different aspects
of random processes and their applications. We also discuss the generality of
the considered models and show that they encompass many well known random
structures and optimization problems to which then the obtained results
automatically apply.