glmmsr
R package glmmsr: Fit a Generalized Linear Mixed Model. Conduct inference about generalized linear mixed models, with a choice about which method to use to approximate the likelihood. In addition to the Laplace and adaptive Gaussian quadrature approximations, which are borrowed from ’lme4’, the likelihood may be approximated by the sequential reduction approximation, or an importance sampling approximation. These methods provide an accurate approximation to the likelihood in some situations where it is not possible to use adaptive Gaussian quadrature.
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References in zbMATH (referenced in 2 articles )
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Sorted by year (- Benjamin Säfken, David Rügamer, Thomas Kneib, Sonja Greven: Conditional Model Selection in Mixed-Effects Models with cAIC4 (2021) not zbMATH
- Bonner, S., Kim, H.-N., Westneat, D., Mutzel, A., Wright, J., Schofield, M.: dalmatian: A Package for Fitting Double Hierarchical Linear Models in R via JAGS and nimble (2021) not zbMATH