{"title":"未知支撑尺寸下的熵估计","authors":"Steffen Schober, Ahmed S. Mansour","doi":"10.1109/ITW.2012.6404729","DOIUrl":null,"url":null,"abstract":"We consider the problem of estimating the entropy of a distribution P of unknown support size N provided with k independently drawn samples, where we are mainly focused on the low sampling regime where k <; N. By extending a method of Hausser and Strimmer [1], which assumes a known support size, by using the support size estimator of Chao and Lee [2], we obtain a simple estimator that performs equally good as the methods of Nemenman, Shafee, and Bialek [3] and Chao and Chen [4].","PeriodicalId":325771,"journal":{"name":"2012 IEEE Information Theory Workshop","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On the estimation of entropy for unknown support size\",\"authors\":\"Steffen Schober, Ahmed S. Mansour\",\"doi\":\"10.1109/ITW.2012.6404729\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider the problem of estimating the entropy of a distribution P of unknown support size N provided with k independently drawn samples, where we are mainly focused on the low sampling regime where k <; N. By extending a method of Hausser and Strimmer [1], which assumes a known support size, by using the support size estimator of Chao and Lee [2], we obtain a simple estimator that performs equally good as the methods of Nemenman, Shafee, and Bialek [3] and Chao and Chen [4].\",\"PeriodicalId\":325771,\"journal\":{\"name\":\"2012 IEEE Information Theory Workshop\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Information Theory Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITW.2012.6404729\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Information Theory Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITW.2012.6404729","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
我们考虑一个未知支持大小N的分布P的熵估计问题，提供k个独立绘制的样本，其中我们主要关注k <;N.通过扩展Hausser和Strimmer[1]的方法，假设支持大小已知，使用Chao和Lee[2]的支持大小估计量，我们得到了一个简单的估计量，其性能与Nemenman, Shafee, and Bialek[3]和Chao和Chen[4]的方法一样好。
On the estimation of entropy for unknown support size
We consider the problem of estimating the entropy of a distribution P of unknown support size N provided with k independently drawn samples, where we are mainly focused on the low sampling regime where k <; N. By extending a method of Hausser and Strimmer [1], which assumes a known support size, by using the support size estimator of Chao and Lee [2], we obtain a simple estimator that performs equally good as the methods of Nemenman, Shafee, and Bialek [3] and Chao and Chen [4].
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