{"title":"Efficient Sampling From the Watson Distribution in Arbitrary Dimensions","authors":"Lukas Sablica, Kurt Hornik, Josef Leydold","doi":"10.1080/10618600.2024.2416521","DOIUrl":null,"url":null,"abstract":"In this paper, we present two efficient methods for sampling from the Watson distribution in arbitrary dimensions. The first method adapts the rejection sampling algorithm from Kent et al. (2018), ...","PeriodicalId":15422,"journal":{"name":"Journal of Computational and Graphical Statistics","volume":"105 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational and Graphical Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/10618600.2024.2416521","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we present two efficient methods for sampling from the Watson distribution in arbitrary dimensions. The first method adapts the rejection sampling algorithm from Kent et al. (2018), ...
期刊介绍：
The Journal of Computational and Graphical Statistics (JCGS) presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December.
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