{"title":"Impact of Time as an Independent in Tree Based Forecasting","authors":"T. Leitch","doi":"10.2139/ssrn.3345995","DOIUrl":null,"url":null,"abstract":"This paper analyzes the impact of including and excluding time when there is a regime change in the explanatory power of a two independent Bernoulli factors driving an observable process Y in order to provide a counterexample illustrating the importance of time as an independent in a tree based forecast.","PeriodicalId":406666,"journal":{"name":"Applied Computing eJournal","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Computing eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3345995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
This paper analyzes the impact of including and excluding time when there is a regime change in the explanatory power of a two independent Bernoulli factors driving an observable process Y in order to provide a counterexample illustrating the importance of time as an independent in a tree based forecast.
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