{"title":"高维伯恩斯坦-冯·米塞斯:简单的例子。","authors":"Iain M Johnstone","doi":"10.1214/10-IMSCOLL607","DOIUrl":null,"url":null,"abstract":"<p><p>In Gaussian sequence models with Gaussian priors, we develop some simple examples to illustrate three perspectives on matching of posterior and frequentist probabilities when the dimension p increases with sample size n: (i) convergence of joint posterior distributions, (ii) behavior of a non-linear functional: squared error loss, and (iii) estimation of linear functionals. The three settings are progressively less demanding in terms of conditions needed for validity of the Bernstein-von Mises theorem.</p>","PeriodicalId":88897,"journal":{"name":"Institute of Mathematical Statistics collections","volume":"6 ","pages":"87-98"},"PeriodicalIF":0.0000,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2990974/pdf/nihms-199314.pdf","citationCount":"0","resultStr":"{\"title\":\"High dimensional Bernstein-von Mises: simple examples.\",\"authors\":\"Iain M Johnstone\",\"doi\":\"10.1214/10-IMSCOLL607\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In Gaussian sequence models with Gaussian priors, we develop some simple examples to illustrate three perspectives on matching of posterior and frequentist probabilities when the dimension p increases with sample size n: (i) convergence of joint posterior distributions, (ii) behavior of a non-linear functional: squared error loss, and (iii) estimation of linear functionals. The three settings are progressively less demanding in terms of conditions needed for validity of the Bernstein-von Mises theorem.</p>\",\"PeriodicalId\":88897,\"journal\":{\"name\":\"Institute of Mathematical Statistics collections\",\"volume\":\"6 \",\"pages\":\"87-98\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2990974/pdf/nihms-199314.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Institute of Mathematical Statistics collections\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1214/10-IMSCOLL607\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Institute of Mathematical Statistics collections","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1214/10-IMSCOLL607","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
High dimensional Bernstein-von Mises: simple examples.
In Gaussian sequence models with Gaussian priors, we develop some simple examples to illustrate three perspectives on matching of posterior and frequentist probabilities when the dimension p increases with sample size n: (i) convergence of joint posterior distributions, (ii) behavior of a non-linear functional: squared error loss, and (iii) estimation of linear functionals. The three settings are progressively less demanding in terms of conditions needed for validity of the Bernstein-von Mises theorem.