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nmw  

Understanding Nonlinear Mixed Effects Modeling for Population Pharmacokinetics
View on CRAN: Click here


Download and install nmw package within the R console
Install from CRAN:
install.packages("nmw")

Install from Github:
library("remotes")
install_github("cran/nmw")

Install by package version:
library("remotes")
install_version("nmw", "0.1.5")



Attach the package and use:
library("nmw")
Maintained by
Kyun-Seop Bae
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-03-14
Latest Update: 2023-05-10
Description:
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.
How to cite:
Kyun-Seop Bae (2017). nmw: Understanding Nonlinear Mixed Effects Modeling for Population Pharmacokinetics. R package version 0.1.5, https://cran.r-project.org/web/packages/nmw
Previous versions and publish date:
0.1.1 (2017-03-14 10:26), 0.1.2 (2017-10-20 07:29), 0.1.4 (2018-04-10 14:54)
Other packages that cited nmw R package
View nmw citation profile
Other R packages that nmw depends, imports, suggests or enhances
Functions, R codes and Examples using the nmw R package
Some associated functions: AddCox . CombDmExPc . CovStep . EstStep . InitStep . MinUtil . Objs . TabStep . TrimOut . e . nmw-package . 
Some associated R codes: AddCox.R . CombDmExPc.R . CovStep.R . EstStep.R . InitStep.R . MinUtil.R . Objs.R . TabStep.R . TrimOut.R .  Full nmw package functions and examples
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