Maximum likelihood estimation in nonlinear mixed effects models

By Estelle Kuhn, Marc Lavielle. Computational Statistics & Data Analysis, 2005

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A feasible implementation procedure for interval analysis method from measurement data (2014, methodology): “The studies of uncertainty quantification based on the probability theory, such as point estimation [36,37], maximum likelihood estimation [38,39], hypothesis testing [40–42], Bayesian method [43–50], etc.”
Semiparametric inference in generalized mixed effects models (2008, background): “Kuhn and Lavielle (2005) extended these to non-linear parametric mixed models.”
Classical Mathematical Models for Description and Prediction of Experimental Tumor Growth (2014, unknown): “expectation maximization (SAEM) algorithm [59].”
A note on BIC in mixed-effects models (2014, methodology): “These calculations can be intricate in nonlinear models but several algorithms are available [11] and are implemented in standard packages.”