{"title":"时间序列模型比较","authors":"Sahil Puri","doi":"10.2139/ssrn.3398018","DOIUrl":null,"url":null,"abstract":"As practitioners, we are not aware of the models that construct the datasets we study. We often rely on intuition to determine which model to choose. This white-paper takes a look at a penitential pitfall: What happens when we use a different model from the actual model generation process?","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time Series Model Comparisons\",\"authors\":\"Sahil Puri\",\"doi\":\"10.2139/ssrn.3398018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As practitioners, we are not aware of the models that construct the datasets we study. We often rely on intuition to determine which model to choose. This white-paper takes a look at a penitential pitfall: What happens when we use a different model from the actual model generation process?\",\"PeriodicalId\":418701,\"journal\":{\"name\":\"ERN: Time-Series Models (Single) (Topic)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Time-Series Models (Single) (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3398018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Time-Series Models (Single) (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3398018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
As practitioners, we are not aware of the models that construct the datasets we study. We often rely on intuition to determine which model to choose. This white-paper takes a look at a penitential pitfall: What happens when we use a different model from the actual model generation process?
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