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The American Statistician Volume 68, 2014 - Issue 2
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Statistical Computing and Graphics

A Note on the Simulation of Overdispersed Random Variables With Specified Marginal Means and Product Correlations

Matthew W. Guerra
&
Justine Shults
Pages 104-107 | Received 01 May 2011, Published online: 20 May 2014

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Read on this site (1)

Wei Jiang, Shuang Song, Lin Hou & Hongyu Zhao. (2021) A Set of Efficient Methods to Generate High-Dimensional Binary Data With Specified Correlation Structures. The American Statistician 75:3, pages 310-322.
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Articles from other publishers (4)

Shaun Bender, Victoria Gamerman, Peter P. Reese, Daniel Lloyd Gray, Yimei Li & Justine Shults. (2021) The first‐order Markov conditional linear expectation approach for analysis of longitudinal data. Statistics in Medicine 40:8, pages 1972-1988.
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Justine Shults. (2017) Simulating longer vectors of correlated binary random variables via multinomial sampling. Computational Statistics & Data Analysis 114, pages 1-11.
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Victoria Gamerman, Matthew Guerra & Justine Shults. (2016) Maximum likelihood based analysis of equally spaced longitudinal count data with first-order antedependence and overdispersion. SpringerPlus 5:1.
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Justine Shults. (2015) Quasi-least squares fitting. Wiley Interdisciplinary Reviews: Computational Statistics 7:3, pages 194-204.
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