Package: nlmixr2extra 5.2.1

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], Omar Elashkar [ctb]

nlmixr2extra_5.2.1.tar.gz
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nlmixr2extra_5.2.1.tar.gz(r-4.7-arm64)nlmixr2extra_5.2.1.tar.gz(r-4.7-x86_64)nlmixr2extra_5.2.1.tar.gz(r-4.6-arm64)nlmixr2extra_5.2.1.tar.gz(r-4.6-x86_64)
nlmixr2extra_5.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
nlmixr2extra/json (API)

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

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

Pkgdown/docs site:https://nlmixr2.github.io

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

On CRAN:

Conda:

openblascpp

7.12 score 7 stars 6 packages 23 scripts 2.2k downloads 47 exports 77 dependencies

Last updated from:fccaccdf6d. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK228
linux-devel-x86_64OK204
source / vignettesOK348
linux-release-arm64OK201
linux-release-x86_64OK216
macos-release-arm64OK147
macos-release-x86_64OK349
macos-oldrel-arm64OK138
macos-oldrel-x86_64OK488
windows-devel-arm64OK264
windows-devel-x86_64OK192
windows-release-arm64OK361
windows-release-x86_64OK237
windows-oldrel-x86_64OK213
wasm-releaseOK162

Exports:aaaNlmixr2ExtraCRANadaptivelassoCoefficientsaddAllEtasaddCatCovariatesaddCovariateaddData2RxaddorremoveCovariateadjustedlassoCoefficientsbootplotbootstrapFitbuildcovInfobuildupatedUIcovarSearchAutofixedControlfoldgengetMinAICFithorseshoeSummardfiivSearchiniisBoundaryFitisLinearizeMatchknit_printlassoCoefficientslassoSummardflinearizelinearizeErrorLineslinearizePlotlinModGenlistModelsTestedllpControlmodelmultistartmultistartControlnlmixrnlmixr2nlmixrFormulanlmixrWithTimingnormalizedDataoptimUnisamplingpreconditionFitprofileFixedprofileFixedSingleprofileLlpregularmodelrerunTopNresSearchrxUiDeparse

Dependencies:armadillo4rbackportsBHcachemcheckmateclicpp11cpp4rcrayondata.tabledigestdparserdplyrevaluatefarverfastmapgenericsggplot2gluegtablehighrinlineisobandknitrL0Learnlabelinglatticelbfgsb3clifecyclelotrimagrittrMASSMatrixmemoiseminqamirain1qn1nanonextnlmenlmixr2datanlmixr2estnumDerivpillarpkgconfigplyrPreciseSumsqs2R6RColorBrewerRcppRcppArmadilloRcppEigenRcppParallelRcppTrustreshape2rexrlangrxode2rxode2lincmtrxode2llS7scalessitmoStanHeadersstringfishstringistringrsymenginesystibbletidyselectutf8vctrsviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
Perform any required data modifications for the nlmixrFormula interface.nlmixrFormulaDataPrep
Expand parameters to include their covariate representations, if applicable..nlmixrFormulaExpandStartParam .nlmixrFormulaExpandStartParamSingle
Parse the formula to extract the dependent variable, predictor, and random effects.nlmixrFormulaParser
Parse the random effects part of a formula.nlmixrFormulaParserRanef
Setup the ini() part of the model for fixed effects.nlmixrFormulaSetupIniFixed .nlmixrFormulaSetupIniRandom
Rename a column in a dataset.renameOrOverwrite
This function is to set the number of threads to 2aaaNlmixr2ExtraCRAN
Return Adaptive lasso coefficients after finding optimal tadaptivelassoCoefficients
Add Individual Random Effects and Fix them to Small ValueaddAllEtas
Make dummy variable cols and updated covarsVecaddCatCovariates
Add Covariate to Model Fit (Generic)addCovariate addCovariate.default addCovariate.nlmixr2FitCore addCovariate.nlmixr2Linearize addCovariate.rxUi
Add Data to RxUi modeladdData2Rx
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
Stepwise Covariate Model-selection (SCM) methodcovarSearchAuto
Generate LaTeX for if blocksextractEqHelper.if
Control options for fixed-value likelihood profilingfixedControl
Stratified cross-validation fold generator function, inspired from the caretfoldgen
Get the model with the minimum Akaike Information Criterion (AIC) valuegetMinAICFit
Create Horseshoe summary posterior estimateshorseshoeSummardf
Automated Inter-Individual Variability SearchiivSearch iivSearch.default iivSearch.nlmixr2Linearize
Detect if a fit has any parameter at the boundaryisBoundaryFit
Check Linearization MatchisLinearizeMatch
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
Perform linearization of a model fitted using FOCEIlinearize
Plot Original Versus Linear Models iObj and EtaslinearizePlot
Generate a Linearization Model From Previous FitlinModGen
Make a list of models tested ready for reportinglistModelsTested
Control options for log-likelihood profilingllpControl
Estimate a model from many starting pointsmultistart multistart.default multistart.function multistart.nlmixr2FitCore multistart.rxUi
Control options for 'multistart()'multistartControl
A simple formula-based interface for nlmixr2nlmixrFormula
Function to return data of normalized covariatesnormalizedData
Sample from uniform distribution by optimoptimUnisampling
Plot a multistart resultplot.nlmixr2Multistart
Linearly re-parameterize the model to be less sensitive to rounding errorspreconditionFit
Print Summary Table For Linearized IIV Searchprint.linIIVSearch
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
Rerun Top N Original Models From A SearchrerunTopN rerunTopN.linIIVSearch
Exhaustively Search for Residual Error ModelresSearch
Example single dose Theophylline ODE modeltheoFitOde