9 citations · 10 across the 6 of their papers we have counts for
3 papers · 1 filter
Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects
Marianne Menictas, Gioia Di Credico, Matt P. Wand
We derive streamlined mean field variational Bayes algorithms for fitting linear mixed models with crossed random effects. In the most general situation, where the dimensions of th…
Streamlined Variational Inference for Higher Level Group-Specific Curve Models
M. Menictas, T. H. Nolan, D. G. Simpson +1
A two-level group-specific curve model is such that the mean response of each member of a group is a separate smooth function of a predictor of interest. The three-level extension…
Streamlined Computing for Variational Inference with Higher Level Random Effects
Tui H. Nolan, Marianne Menictas, Matt P. Wand
We derive and present explicit algorithms to facilitate streamlined computing for variational inference for models containing higher level random effects. Existing literature, such…