A Skew‐normal copula‐driven GLMM |
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| Authors: | Kalyan Das Mohamad Elmasri Arusharka Sen |
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| Affiliation: | 1. Department of Statistics University of Calcutta 35, Kolkata, India;2. Department of Mathematics and Statistics McGill University Burnside Hall, QC, Canada;3. S‐LB 921‐23 J.W. McConnell Building, 1400 De Maisonneuve W. Montreal, QC, Canada |
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| Abstract: | This paper presents a method for fitting a copula‐driven generalized linear mixed models. For added flexibility, the skew‐normal copula is adopted for fitting. The correlation matrix of the skew‐normal copula is used to capture the dependence structure within units, while the fixed and random effects coefficients are estimated through the mean of the copula. For estimation, a Monte Carlo expectation–maximization algorithm is developed. Simulations are shown alongside a real data example from the Framingham Heart Study. |
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| Keywords: | EM algorithm Gaussian copula generalized linear mixed models Monte Carlo skew‐normal. |
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