Consider the linear mixed model with normal random effects,
Y = Xβ + Zv + ε
where β and v are vectors of fixed and random effects. One of most popular methods to solve the Henderson's Mixed Model Equation related to the problem is EM-type algorithm. Its drawback, however, comes from repetitive matrix inversion during recursive estimation steps. Kim (2017) proposed a novel method of avoiding such difficulty, letting the estimation more fast, stable, and scalable.
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