{"title":"Model selection in continuous time","authors":"L. Gerencsér, Z. Vágó","doi":"10.1109/CDC.1991.261466","DOIUrl":null,"url":null,"abstract":"The foundations of a theory of model selection for continuous-time autoregressive systems is outlined. The authors define the predictive stochastic complexity for continuous-time systems and investigate its asymptotic properties. An almost sure asymptotic result is presented.<<ETX>>","PeriodicalId":344553,"journal":{"name":"[1991] Proceedings of the 30th IEEE Conference on Decision and Control","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings of the 30th IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1991.261466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The foundations of a theory of model selection for continuous-time autoregressive systems is outlined. The authors define the predictive stochastic complexity for continuous-time systems and investigate its asymptotic properties. An almost sure asymptotic result is presented.<>
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