Efficient Sampling From the Watson Distribution in Arbitrary Dimensions

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-10-23 DOI:10.1080/10618600.2024.2416521

Lukas Sablica, Kurt Hornik, Josef Leydold

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), ...

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从任意维度的沃森分布中高效取样

本文提出了两种从任意维度的沃森分布中采样的高效方法。第一种方法采用了 Kent 等人（2018）的拒绝采样算法， ...

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来源期刊

Journal of Computational and Graphical Statistics 数学-统计学与概率论

CiteScore

3.50

自引率

8.30%

发文量

153

审稿时长

>12 weeks

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.