3 citations · 3 across the 7 of their papers we have counts for
4 papers · 2 filters
High-dimensional sliced inverse regression with endogeneity
Linh H. Nghiem, Francis. K. C. Hui, Samuel Muller +1
Sliced inverse regression (SIR) is a popular sufficient dimension reduction method that identifies a few linear transformations of the covariates without losing regression informat…
Random Effects Misspecification and its Consequences for Prediction in Generalized Linear Mixed Models
Quan Vu, Francis K. C. Hui, Samuel Muller +1
When fitting generalized linear mixed models (GLMMs), one important decision to make relates to the choice of the random effects distribution. As the random effects are unobserved,…
Robust Linear Mixed Models using Hierarchical Gamma-Divergence
Shonosuke Sugasawa, Francis K. C. Hui, Alan H. Welsh
Linear mixed models (LMMs) are a popular class of methods for analyzing longitudinal and clustered data. However, such models can be sensitive to outliers, and this can lead to bia…
Restricted maximum likelihood estimation in generalized linear mixed models
Luca Maestrini, Francis K. C. Hui, Alan H. Welsh
Restricted maximum likelihood (REML) estimation is a widely accepted and frequently used method for fitting linear mixed models, with its principal advantage being that it produces…