{"title":"用微分积分法推广了斯坦引理","authors":"Konstantinos Mamis","doi":"10.1016/j.exco.2022.100077","DOIUrl":null,"url":null,"abstract":"<div><p>We extend Stein’s lemma for averages that explicitly contain the Gaussian random variable at a power. We present two proofs for this extension of Stein’s lemma, with the first being a rigorous proof by mathematical induction. The alternative, second proof is a constructive formal derivation in which we express the average not as an integral, but as the action of a pseudodifferential operator defined via the Gaussian moment-generating function. In extended Stein’s lemma, the absolute values of the coefficients of the probabilist’s Hermite polynomials appear, revealing yet another link between Hermite polynomials and normal distribution.</p></div>","PeriodicalId":100517,"journal":{"name":"Examples and Counterexamples","volume":"2 ","pages":"Article 100077"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666657X22000143/pdfft?md5=a843ad26cd9ee26552cd2b455011ed66&pid=1-s2.0-S2666657X22000143-main.pdf","citationCount":"3","resultStr":"{\"title\":\"Extension of Stein’s lemma derived by using an integration by differentiation technique\",\"authors\":\"Konstantinos Mamis\",\"doi\":\"10.1016/j.exco.2022.100077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We extend Stein’s lemma for averages that explicitly contain the Gaussian random variable at a power. We present two proofs for this extension of Stein’s lemma, with the first being a rigorous proof by mathematical induction. The alternative, second proof is a constructive formal derivation in which we express the average not as an integral, but as the action of a pseudodifferential operator defined via the Gaussian moment-generating function. In extended Stein’s lemma, the absolute values of the coefficients of the probabilist’s Hermite polynomials appear, revealing yet another link between Hermite polynomials and normal distribution.</p></div>\",\"PeriodicalId\":100517,\"journal\":{\"name\":\"Examples and Counterexamples\",\"volume\":\"2 \",\"pages\":\"Article 100077\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666657X22000143/pdfft?md5=a843ad26cd9ee26552cd2b455011ed66&pid=1-s2.0-S2666657X22000143-main.pdf\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Examples and Counterexamples\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666657X22000143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Examples and Counterexamples","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666657X22000143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extension of Stein’s lemma derived by using an integration by differentiation technique
We extend Stein’s lemma for averages that explicitly contain the Gaussian random variable at a power. We present two proofs for this extension of Stein’s lemma, with the first being a rigorous proof by mathematical induction. The alternative, second proof is a constructive formal derivation in which we express the average not as an integral, but as the action of a pseudodifferential operator defined via the Gaussian moment-generating function. In extended Stein’s lemma, the absolute values of the coefficients of the probabilist’s Hermite polynomials appear, revealing yet another link between Hermite polynomials and normal distribution.