{"title":"使用保形二次样条生成随机数","authors":"D. McAllister, J. Roulier, M. Evans","doi":"10.1145/503643.503691","DOIUrl":null,"url":null,"abstract":"Let F be an arbitrary continuous cumulative distribution function of a single variable specified by a finite set of points. A (smooth) increasing quadratic spline is constructed which interpolates the data points and preserves the convexity of the data [2]. The spline is compared with Akima's piecewise cubic approximation [1] for several common distributions F.","PeriodicalId":166583,"journal":{"name":"Proceedings of the 16th annual Southeast regional conference","volume":"30 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1978-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Generation of random numbers using shape preserving quadratic splines\",\"authors\":\"D. McAllister, J. Roulier, M. Evans\",\"doi\":\"10.1145/503643.503691\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Let F be an arbitrary continuous cumulative distribution function of a single variable specified by a finite set of points. A (smooth) increasing quadratic spline is constructed which interpolates the data points and preserves the convexity of the data [2]. The spline is compared with Akima's piecewise cubic approximation [1] for several common distributions F.\",\"PeriodicalId\":166583,\"journal\":{\"name\":\"Proceedings of the 16th annual Southeast regional conference\",\"volume\":\"30 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1978-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 16th annual Southeast regional conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/503643.503691\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th annual Southeast regional conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/503643.503691","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generation of random numbers using shape preserving quadratic splines
Let F be an arbitrary continuous cumulative distribution function of a single variable specified by a finite set of points. A (smooth) increasing quadratic spline is constructed which interpolates the data points and preserves the convexity of the data [2]. The spline is compared with Akima's piecewise cubic approximation [1] for several common distributions F.