From 2a028c96b7f280ed0f77ca1a2cd42b074821e484 Mon Sep 17 00:00:00 2001 From: Matthew Fidler Date: Sat, 21 Sep 2024 21:54:14 -0500 Subject: [PATCH] Fix utls --- README.Rmd | 2 +- README.md | 2 +- inst/CITATION | 7 ++----- 3 files changed, 4 insertions(+), 7 deletions(-) diff --git a/README.Rmd b/README.Rmd index 3bc81bea..51fc4f8d 100644 --- a/README.Rmd +++ b/README.Rmd @@ -73,7 +73,7 @@ Babelmixr2 can help you by: While not required, you can get/install the R 'lixoftConnectors' package in the 'Monolix' installation, as described at the following url -. When +. When 'lixoftConnectors' is available, R can run 'Monolix' directly instead of using a command line. diff --git a/README.md b/README.md index 6ade880d..3e8386ac 100644 --- a/README.md +++ b/README.md @@ -68,7 +68,7 @@ Babelmixr2 can help you by: While not required, you can get/install the R ‘lixoftConnectors’ package in the ‘Monolix’ installation, as described at the following url -. +. When ‘lixoftConnectors’ is available, R can run ‘Monolix’ directly instead of using a command line. diff --git a/inst/CITATION b/inst/CITATION index 5e9f57a1..50775fd5 100644 --- a/inst/CITATION +++ b/inst/CITATION @@ -57,8 +57,7 @@ bibentry(bibtype="Article", month = "sep", abstract = "nlmixr is a free and open-source R package for fitting nonlinear pharmacokinetic (PK), pharmacodynamic (PD), joint PK-PD, and quantitative systems pharmacology mixed-effects models. Currently, nlmixr is capable of fitting both traditional compartmental PK models as well as more complex models implemented using ordinary differential equations. We believe that, over time, it will become a capable, credible alternative to commercial software tools, such as NONMEM, Monolix, and Phoenix NLME.", address ="Hoboken", - publisher = "John Wiley and Sons Inc.", - url = "https://doi.org/10.1002/psp4.12445") + publisher = "John Wiley and Sons Inc.") bibentry(bibtype="Article", title="Performance of the SAEM and FOCEI Algorithms in the Open-Source, Nonlinear Mixed Effect Modeling Tool nlmixr", @@ -89,6 +88,4 @@ bibentry(bibtype="Article", pages = "923--930", number = "12", month = "dec", - abstract="The free and open-source package nlmixr implements pharmacometric nonlinear mixed effects model parameter estimation in R. It provides a uniform language to define pharmacometric models using ordinary differential equations. Performances of the stochastic approximation expectation-maximization (SAEM) and first order-conditional estimation with interaction (FOCEI) algorithms in nlmixr were compared with those found in the industry standards, Monolix and NONMEM, using the following two scenarios: a simple model fit to 500 sparsely sampled data sets and a range of more complex compartmental models with linear and nonlinear clearance fit to data sets with rich sampling. Estimation results obtained from nlmixr for FOCEI and SAEM matched the corresponding output from NONMEM/FOCEI and Monolix/SAEM closely both in terms of parameter estimates and associated standard errors. These results indicate that nlmixr may provide a viable alternative to existing tools for pharmacometric parameter estimation.", - url="https://doi.org/10.1002/psp4.12471" - ) + abstract="The free and open-source package nlmixr implements pharmacometric nonlinear mixed effects model parameter estimation in R. It provides a uniform language to define pharmacometric models using ordinary differential equations. Performances of the stochastic approximation expectation-maximization (SAEM) and first order-conditional estimation with interaction (FOCEI) algorithms in nlmixr were compared with those found in the industry standards, Monolix and NONMEM, using the following two scenarios: a simple model fit to 500 sparsely sampled data sets and a range of more complex compartmental models with linear and nonlinear clearance fit to data sets with rich sampling. Estimation results obtained from nlmixr for FOCEI and SAEM matched the corresponding output from NONMEM/FOCEI and Monolix/SAEM closely both in terms of parameter estimates and associated standard errors. These results indicate that nlmixr may provide a viable alternative to existing tools for pharmacometric parameter estimation.")