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Journal of Statistical Computation and Simulation Volume 81, 2011 - Issue 4
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Original Articles

Evaluation of algorithms for generating Dirichlet random vectors

Y. C. Hung Department of Statistics, National Chengchi University, Taipei, 11605, Taiwan, Republic of ChinaCorrespondence[email protected]
,
N. Balakrishnan Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada, L8S 4K1
&
C. W. Cheng Graduate Institute of Statistics, National Central University, Jhongli, 32049, Taiwan, Republic of China
Pages 445-459 | Received 27 May 2009, Accepted 12 Oct 2009, Published online: 02 Jun 2010

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Read on this site (2)

Aylin Alin. (2014) Adjusted power-divergence test statistics for simple goodness-of-fit under clustered sampling. Journal of Statistical Computation and Simulation 84:9, pages 1904-1916.
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Jakob Bergman. (2012) Generating random variates from a bicompositional Dirichlet distribution. Journal of Statistical Computation and Simulation 82:6, pages 797-805.
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Articles from other publishers (3)

Ying‐Chao Hung. (2023) A review of Monte Carlo and quasi‐Monte Carlo sampling techniques . WIREs Computational Statistics.
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Alexander Davis, Ruli Gao & Nicholas E. Navin. (2019) SCOPIT: sample size calculations for single-cell sequencing experiments. BMC Bioinformatics 20:1.
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Ching-Wei Cheng, Ying-Chao Hung & Narayanaswamy Balakrishnan. (2014) Generating beta random numbers and Dirichlet random vectors in R: The package rBeta2009. Computational Statistics & Data Analysis 71, pages 1011-1020.
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