{"title":"分位数回归中的重点模型选择","authors":"P. Behl, G. Claeskens, H. Dette","doi":"10.2139/ssrn.2244943","DOIUrl":null,"url":null,"abstract":"We consider the problem of model selection for quantile regression analysis where a particular purpose of the modeling procedure has to be taken into account. Typical examples include estimation of the area under the curve in pharmacokinetics or estimation of the minimum eff ective dose in phase II clinical trials. A focused information criterion for quantile regression is developed, analyzed and investigated by means of a simulation study and data analysis.","PeriodicalId":163739,"journal":{"name":"ERN: Model Construction & Selection (Topic)","volume":"135 2-3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"Focused Model Selection in Quantile Regression\",\"authors\":\"P. Behl, G. Claeskens, H. Dette\",\"doi\":\"10.2139/ssrn.2244943\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider the problem of model selection for quantile regression analysis where a particular purpose of the modeling procedure has to be taken into account. Typical examples include estimation of the area under the curve in pharmacokinetics or estimation of the minimum eff ective dose in phase II clinical trials. A focused information criterion for quantile regression is developed, analyzed and investigated by means of a simulation study and data analysis.\",\"PeriodicalId\":163739,\"journal\":{\"name\":\"ERN: Model Construction & Selection (Topic)\",\"volume\":\"135 2-3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-01-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Model Construction & Selection (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2244943\",\"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: Model Construction & Selection (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2244943","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We consider the problem of model selection for quantile regression analysis where a particular purpose of the modeling procedure has to be taken into account. Typical examples include estimation of the area under the curve in pharmacokinetics or estimation of the minimum eff ective dose in phase II clinical trials. A focused information criterion for quantile regression is developed, analyzed and investigated by means of a simulation study and data analysis.
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