{"title":"预测与随机选择","authors":"Pathikrit Basu","doi":"10.2139/ssrn.3338991","DOIUrl":null,"url":null,"abstract":"In this paper, we study a non-parametric approach to prediction in stochastic choice models in economics. We show that VC complexity characterises the predictability of stochastic choice models. We establish prediction methods and provide corresponding rates of convergence.<br>","PeriodicalId":319981,"journal":{"name":"ERN: Stochastic & Dynamic Games (Topic)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction and Stochastic Choice\",\"authors\":\"Pathikrit Basu\",\"doi\":\"10.2139/ssrn.3338991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we study a non-parametric approach to prediction in stochastic choice models in economics. We show that VC complexity characterises the predictability of stochastic choice models. We establish prediction methods and provide corresponding rates of convergence.<br>\",\"PeriodicalId\":319981,\"journal\":{\"name\":\"ERN: Stochastic & Dynamic Games (Topic)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Stochastic & Dynamic Games (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3338991\",\"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: Stochastic & Dynamic Games (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3338991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we study a non-parametric approach to prediction in stochastic choice models in economics. We show that VC complexity characterises the predictability of stochastic choice models. We establish prediction methods and provide corresponding rates of convergence.
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