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nmw: Understanding Nonlinear Mixed Effects Modeling for Population Pharmacokinetics
This shows how NONMEM(R) software works. NONMEM's classical estimation methods like 'First Order(FO) approximation', 'First Order Conditional Estimation(FOCE)', and 'Laplacian approximation' are explained. Additionally, provides functions for post-run processing of NONMEM output files, generating comprehensive PDF diagnostic reports including objective function value analysis, parameter estimates, prediction diagnostics, residual diagnostics, empirical Bayes estimate (EBE) analysis, input data summary, and individual pharmacokinetic parameter distributions.
Getting started
Browse package contents
Package details |
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| Author | Kyun-Seop Bae [aut, cre] |
| Maintainer | Kyun-Seop Bae <k@acr.kr> |
| License | GPL-3 |
| Version | 0.3.0 |
| URL | https://cran.r-project.org/package=nmw |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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