A composite-likelihood EM algorithm with importance sampling yields computationally feasible, asymptotically valid inference for the Poisson log-normal model on moderately large multivariate count datasets.
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Composite likelihood inference for the Poisson log-normal model
A composite-likelihood EM algorithm with importance sampling yields computationally feasible, asymptotically valid inference for the Poisson log-normal model on moderately large multivariate count datasets.