Package: nlmixr2extra 3.0.1.9000

Matthew Fidler

nlmixr2extra: Nonlinear Mixed Effects Models in Population PK/PD, Extra Support Functions

Fit and compare nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation solving is by compiled C code provided in the 'rxode2' package (Wang, Hallow, and James 2015 <doi:10.1002/psp4.12052>). This package is for support functions like preconditioned fits <doi:10.1208/s12248-016-9866-5>, boostrap and stepwise covariate selection.

Authors:Matthew Fidler [aut, cre], Vipul Mann [aut], Vishal Sarsani [aut], Christian Bartels [ctb], Bill Denney [aut]

nlmixr2extra_3.0.1.9000.tar.gz
nlmixr2extra_3.0.1.9000.zip(r-4.5)nlmixr2extra_3.0.1.9000.zip(r-4.4)nlmixr2extra_3.0.1.9000.zip(r-4.3)
nlmixr2extra_3.0.1.9000.tgz(r-4.4-x86_64)nlmixr2extra_3.0.1.9000.tgz(r-4.4-arm64)nlmixr2extra_3.0.1.9000.tgz(r-4.3-x86_64)nlmixr2extra_3.0.1.9000.tgz(r-4.3-arm64)
nlmixr2extra_3.0.1.9000.tar.gz(r-4.5-noble)nlmixr2extra_3.0.1.9000.tar.gz(r-4.4-noble)
nlmixr2extra_3.0.1.9000.tgz(r-4.4-emscripten)nlmixr2extra_3.0.1.9000.tgz(r-4.3-emscripten)
nlmixr2extra.pdf |nlmixr2extra.html✨
nlmixr2extra/json (API)
NEWS

# Install 'nlmixr2extra' in R:
install.packages('nlmixr2extra', repos = c('https://nlmixr2.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/nlmixr2/nlmixr2extra/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • theoFitOde - Example single dose Theophylline ODE model

On CRAN:

5.84 score 3 stars 5 packages 11 scripts 1.7k downloads 28 exports 82 dependencies

Last updated 2 days agofrom:efd9a32534. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-win-x86_64OKNov 21 2024
R-4.5-linux-x86_64OKNov 21 2024
R-4.4-win-x86_64OKNov 21 2024
R-4.4-mac-x86_64OKNov 21 2024
R-4.4-mac-aarch64OKNov 21 2024
R-4.3-win-x86_64OKNov 21 2024
R-4.3-mac-x86_64OKNov 21 2024
R-4.3-mac-aarch64OKNov 21 2024

Exports:adaptivelassoCoefficientsaddCatCovariatesaddorremoveCovariateadjustedlassoCoefficientsbootplotbootstrapFitbuildcovInfobuildupatedUIfixedControlfoldgenhorseshoeSummardfiniknit_printlassoCoefficientslassoSummardfllpControlmodelnlmixrnlmixr2nlmixrWithTimingnormalizedDataoptimUnisamplingpreconditionFitprofileFixedprofileFixedSingleprofileLlpregularmodelrxUiDeparse

Dependencies:backportsBHcachemcheckmateclicolorspacecommonmarkcpp11cpp11armadillocrayoncurldata.tabledigestdparserdplyrevaluatefansifarverfastmapgenericsggplot2ggtextgluegridtextgtablehighrinlineisobandjpegknitrlabelinglatticelazyevallbfgsb3clifecyclelotrimagrittrmarkdownMASSMatrixmemoisemgcvminqamunselln1qn1nlmenlmixr2datanlmixr2estnumDerivpillarpkgconfigpngPreciseSumsqsR6RApiSerializeRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrexrlangrxode2rxode2llscalessitmoStanHeadersstringfishstringistringrsymenginesystibbletidyselectutf8vctrsviridisLitewithrxfunxml2yaml

Readme and manuals

Help Manual

Help pageTopics
Return Adaptive lasso coefficients after finding optimal tadaptivelassoCoefficients
Make dummy variable cols and updated covarsVecaddCatCovariates
Add covariateaddorremoveCovariate
Return Adjusted adaptive lasso coefficients after finding optimal tadjustedlassoCoefficients
Produce delta objective function for boostrapbootplot bootplot.nlmixr2FitCore
Bootstrap nlmixr2 fitbootstrapFit
Build covInfo list from varsVec and covarsVecbuildcovInfo
Build updated from the covariate and variable vector listbuildupatedUI
Control options for fixed-value likelihood profilingfixedControl
Stratified cross-validation fold generator function, inspired from the caretfoldgen
Create Horseshoe summary posterior estimateshorseshoeSummardf
Extract the equations from an nlmixr2/rxode2 model to produce a 'LaTeX' equation.knit_print.nlmixr2FitCore knit_print.rxUi
Return Final lasso coefficients after finding optimal tlassoCoefficients
Create Lasso summary posterior estimateslassoSummardf
Control options for log-likelihood profilingllpControl
Function to return data of normalized covariatesnormalizedData
Sample from uniform distribution by optimoptimUnisampling
Linearly re-parameterize the model to be less sensitive to rounding errorspreconditionFit
Perform likelihood profiling on nlmixr2 focei fitsprofile.nlmixr2FitCore
Estimate the objective function values for a model while fixing defined parameter valuesprofileFixed profileFixedSingle
Profile confidence intervals with log-likelihood profilingprofileLlp
Give the output data.frame for a single model for profile.nlmixr2FitCoreprofileNlmixr2FitCoreRet
Regular lasso modelregularmodel
Example single dose Theophylline ODE modeltheoFitOde