{"title":"Robust Parametric Inference","authors":"J. Racine","doi":"10.1093/OSO/9780190900663.003.0004","DOIUrl":null,"url":null,"abstract":"This chapter looks at alternatives to the use of asymptotic theory and finite-sample theory for the purpose of inference. It considers numerical approaches that include the bootstrap and the Jackknife and considers procedures for dependent processes as well as heteroskedastic and independent identically distributed instances.","PeriodicalId":244208,"journal":{"name":"Reproducible Econometrics Using R","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Reproducible Econometrics Using R","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/OSO/9780190900663.003.0004","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 chapter looks at alternatives to the use of asymptotic theory and finite-sample theory for the purpose of inference. It considers numerical approaches that include the bootstrap and the Jackknife and considers procedures for dependent processes as well as heteroskedastic and independent identically distributed instances.
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