{"title":"评估密度预测:评论","authors":"A. Tsyplakov","doi":"10.2139/ssrn.1907799","DOIUrl":null,"url":null,"abstract":"This is a comment on Mitchell and Wallis (2011) which in turn is a critical reaction to Gneiting et al. (2007). The comment discusses the notion of forecast calibration, the advantage of using scoring rules, the “sharpness” principle and a general approach to testing calibration. The aim is to show how a more general and explicitly stated framework can provide further insights into the theory and practice of of probabilistic forecasting.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"6 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2011-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Evaluating Density Forecasts: A Comment\",\"authors\":\"A. Tsyplakov\",\"doi\":\"10.2139/ssrn.1907799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This is a comment on Mitchell and Wallis (2011) which in turn is a critical reaction to Gneiting et al. (2007). The comment discusses the notion of forecast calibration, the advantage of using scoring rules, the “sharpness” principle and a general approach to testing calibration. The aim is to show how a more general and explicitly stated framework can provide further insights into the theory and practice of of probabilistic forecasting.\",\"PeriodicalId\":11485,\"journal\":{\"name\":\"Econometrics: Applied Econometrics & Modeling eJournal\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometrics: Applied Econometrics & Modeling eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.1907799\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometrics: Applied Econometrics & Modeling eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.1907799","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This is a comment on Mitchell and Wallis (2011) which in turn is a critical reaction to Gneiting et al. (2007). The comment discusses the notion of forecast calibration, the advantage of using scoring rules, the “sharpness” principle and a general approach to testing calibration. The aim is to show how a more general and explicitly stated framework can provide further insights into the theory and practice of of probabilistic forecasting.
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