Understanding Nonlinear Mixed Effects Modeling for Population Pharmacokinetics

This shows how 'NONMEM' (Beal SL, Sheiner LB, Boeckmann AJ, Bauer RJ. NONMEM 7.5 Users Guides. Icon plc, 2020) software works. 'NONMEM' classical estimation methods such as 'First Order (FO) approximation', 'First Order Conditional Estimation (FOCE)', and 'Laplacian approximation' are explained. Functions are also provided for post-run processing of NONMEM output files, generating PDF or Markdown diagnostic reports including objective function value analysis, parameter estimates, prediction and residual diagnostics, empirical Bayes estimate (EBE) analysis, input data summary, and individual pharmacokinetic parameter distributions. Helper utilities for building NONMEM-ready datasets from SDTM-style source tables are also included.


Reference manual

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install.packages("nmw")

0.6.0 by Kyun-Seop Bae, 19 days ago


https://cran.r-project.org/package=nmw


Browse source code at https://github.com/cran/nmw


Authors: Kyun-Seop Bae [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports simPDF, MASS, grDevices, graphics, stats, utils

Depends on numDeriv

Suggests testthat


See at CRAN