The Sampling/Importance Resampling Algorithm
2004; Wiley; Linguagem: Inglês
10.1002/0470090456.ch24
ISSN1940-6347
Autores Tópico(s)Bayesian Methods and Mixture Models
ResumoChapter 24 The Sampling/Importance Resampling Algorithm Kim-Hung Li, Kim-Hung Li Department of Statistics, Chinese University of Hong Kong, Shatin, N.T., Hong KongSearch for more papers by this author Kim-Hung Li, Kim-Hung Li Department of Statistics, Chinese University of Hong Kong, Shatin, N.T., Hong KongSearch for more papers by this author Book Editor(s):Andrew Gelman, Andrew Gelman Department of Statistics and Department of Political Science, Columbia University, New York, USASearch for more papers by this authorXiao-Li Meng, Xiao-Li Meng Department of Statistics, Harvard University, USASearch for more papers by this author First published: 23 July 2004 https://doi.org/10.1002/0470090456.ch24Citations: 2Book Series:Wiley Series in Probability and Statistics Series Editor(s): Walter A. Shewhart, Walter A. ShewhartSearch for more papers by this authorSamuel S. Wilks, Samuel S. WilksSearch for more papers by this author AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Summary This chapter contains sections titled: Introduction SIR algorithm Selection of the pool size Selection criterion of the importance sampling distribution The resampling algorithms Discussion Citing Literature Applied Bayesian Modeling and Causal Inference from Incomplete‐Data Perspectives: An Essential Journey with Donald Rubin's Statistical Family RelatedInformation
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