Package: xpose4 4.7.3

Andrew C. Hooker

xpose4: Diagnostics for Nonlinear Mixed-Effect Models

A model building aid for nonlinear mixed-effects (population) model analysis using NONMEM, facilitating data set checkout, exploration and visualization, model diagnostics, candidate covariate identification and model comparison. The methods are described in Keizer et al. (2013) <doi:10.1038/psp.2013.24>, and Jonsson et al. (1999) <doi:10.1016/s0169-2607(98)00067-4>.

Authors:Andrew C. Hooker [aut, cre, cph], Mats O. Karlsson [aut, cph], Justin J. Wilkins [aut], E. Niclas Jonsson [aut, trl, cph], Ron Keizer [ctb]

xpose4_4.7.3.tar.gz
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xpose4_4.7.3.tgz(r-4.4-any)xpose4_4.7.3.tgz(r-4.3-any)
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xpose4.pdf |xpose4.html
xpose4/json (API)
NEWS

# Install 'xpose4' in R:
install.packages('xpose4', repos = c('https://uupharmacometrics.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/uupharmacometrics/xpose4/issues

Datasets:

On CRAN:

diagnosticsnonmempharmacometricspopulation-modelxpose

7.28 score 34 stars 311 scripts 696 downloads 9 mentions 199 exports 85 dependencies

Last updated 9 months agofrom:f79acaed4c. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winNOTEOct 31 2024
R-4.5-linuxNOTEOct 31 2024
R-4.4-winOKOct 31 2024
R-4.4-macOKOct 31 2024
R-4.3-winOKOct 31 2024
R-4.3-macOKOct 31 2024

Exports:absval.cwres.vs.cov.bwabsval.cwres.vs.predabsval.cwres.vs.pred.by.covabsval.dcwres.vs.cov.model.compabsval.dipred.vs.cov.model.compabsval.diwres.vs.cov.model.compabsval.dpred.vs.cov.model.compabsval.dwres.vs.cov.model.compabsval.iwres.cwres.vs.ipred.predabsval.iwres.vs.cov.bwabsval.iwres.vs.idvabsval.iwres.vs.ipredabsval.iwres.vs.ipred.by.covabsval.iwres.vs.predabsval.iwres.wres.vs.ipred.predabsval.wres.vs.cov.bwabsval.wres.vs.idvabsval.wres.vs.predabsval.wres.vs.pred.by.covadd.absvaladd.dichotadd.expadd.grid.tableadd.logadd.model.compadd.tadaddit.gofautocorr.cwresautocorr.iwresautocorr.wresbasic.gofbasic.model.compboot.histbootgam.printbootscm.importcalc.nparcat.dv.vs.idv.sbcat.pcchange.ab.graph.parchange.bw.graph.parchange.cat.contchange.cat.cont<-change.cat.levelschange.cat.levels<-change.cond.graph.parchange.dil.graph.parchange.dv.cat.levelschange.dv.cat.levels<-change.label.parchange.lm.graph.parchange.misc.graph.parchange.misschange.parmchange.pi.graph.parchange.smooth.graph.parchange.subsetchange.var.namechange.xlabelchange.xvardefchange.xvardef<-compute.cwrescov.histcov.qqcov.splomcov.summarycreate.parameter.listcreate.xpose.plot.classescreateXposeClassescwres.dist.histcwres.dist.qqcwres.vs.covcwres.vs.idvcwres.vs.idv.bwcwres.vs.predcwres.vs.pred.bwcwres.wres.vs.idvcwres.wres.vs.predDatadata.checkoutData<-db.namesdOFV.vs.covdOFV.vs.iddOFV1.vs.dOFV2dv.preds.vs.idvdv.vs.idvdv.vs.ipreddv.vs.ipred.by.covdv.vs.ipred.by.idvdv.vs.preddv.vs.pred.by.covdv.vs.pred.by.idvdv.vs.pred.ipredexport.graph.parexport.variable.definitionsget.docgofimport.graph.parimport.variable.definitionsind.plotsind.plots.cwres.histind.plots.cwres.qqind.plots.wres.histind.plots.wres.qqipred.vs.idviwres.dist.histiwres.dist.qqiwres.vs.idvkaplan.plotmake.sb.datanpc.coveragensimparm.histparm.qqparm.splomparm.summaryparm.vs.covparm.vs.parmpred.vs.idvrandtest.histranpar.histranpar.qqranpar.splomranpar.vs.covread_nm_tableread.lstread.nm.tablesread.npc.vpc.resultsread.TTE.sim.dataread.vpctabrunsumSDataSData<-set.docsimprazExampletabulate.parameterswres.dist.histwres.dist.qqwres.vs.covwres.vs.idvwres.vs.idv.bwwres.vs.predwres.vs.pred.bwxlabelxlabel<-xp.akaike.plotxp.boot.par.estxp.boot.par.est.corrxp.cookxp.daic.npar.plotxp.distr.mod.sizexp.dofv.npar.plotxp.dofv.plotxp.get.dispxp.inc.cond.stab.covxp.inc.ind.cond.stab.covxp.inc.probxp.inc.prob.comb.2xp.inc.stab.covxp.incl.index.covxp.incl.index.cov.compxp.incl.index.cov.indxp.ind.inf.fitxp.ind.inf.termsxp.ind.stud.resxp.plotxp.scope3xp.summaryxpose.bootgamxpose.calculate.cwresxpose.dataxpose.gamxpose.license.citationxpose.logTicksxpose.multiple.plotxpose.multiple.plot.defaultxpose.panel.bwxpose.panel.defaultxpose.panel.histogramxpose.panel.qqxpose.panel.splomxpose.plot.bwxpose.plot.defaultxpose.plot.histogramxpose.plot.qqxpose.plot.splomxpose.printxpose.string.printxpose.VPCxpose.VPC.bothxpose.VPC.categoricalxpose.writexpose.xscale.components.log10xpose.yscale.components.log10xpose4xsubsetxsubset<-xvardefxvardef<-

Dependencies:backportsbase64encbitbit64bslibcachemcheckmateclicliprclustercodetoolscolorspacecpp11crayondata.tabledigestdplyrevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsgamgenericsggplot2gluegridExtragtablehighrHmischmshtmlTablehtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonliteknitrlabelinglatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmennetpillarpkgconfigprettyunitsprogressR6rappdirsRColorBrewerreadrrlangrmarkdownrpartrstudioapisassscalesstringistringrsurvivaltibbletidyselecttinytextzdbutf8vctrsviridisviridisLitevroomwithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
The Xpose Packagexpose4-package xpose
Model comparison plots, of absolute differences in goodness-of-fit predictors against covariates, for Xpose 4absval.dcwres.vs.cov.model.comp absval.dipred.vs.cov.model.comp absval.diwres.vs.cov.model.comp absval.dpred.vs.cov.model.comp absval.dwres.vs.cov.model.comp absval_delta_vs_cov_model_comp
Absolute conditional weighted residuals vs covariates for Xpose 4absval.cwres.vs.cov.bw
Absolute population conditional weighted residuals vs population predictions for Xpose 4absval.cwres.vs.pred
Absolute value of the conditional weighted residuals vs. population predictions, conditioned on covariates, for Xpose 4absval.cwres.vs.pred.by.cov
Absolute population weighted residuals vs population predictions, and absolute individual weighted residuals vs individual predictions, for Xpose 4absval.iwres.cwres.vs.ipred.pred absval.iwres.wres.vs.ipred.pred
box and whisker plots of the absolute value of the individual weighted residuals vs. covariatesabsval.iwres.vs.cov.bw
absolute value of the individual weighted residuals vs. the independent variableabsval.iwres.vs.idv
Absolute individual weighted residuals vs individual predictions for Xpose 4absval.iwres.vs.ipred
Absolute individual weighted residuals vs individual predictions, conditioned on covariates, for Xpose 4absval.iwres.vs.ipred.by.cov
Absolute individual weighted residuals vs population predictions or independent variable for Xpose 4absval.iwres.vs.pred
Absolute weighted residuals vs covariates for Xpose 4absval.wres.vs.cov.bw
Absolute value of (C)WRES vs. independent variable plot in Xpose4.absval.wres.vs.idv
Absolute population weighted residuals vs population predictions for Xpose 4absval.wres.vs.pred
Absolute population weighted residuals vs population predictions, conditioned on covariates, for Xpose 4absval.wres.vs.pred.by.cov
Column-transformation functions for Xpose 4add.absval add.dichot add.exp add.log add.tad add_transformed_columns
Print tables or text in a grid objectadd.grid.table add.grid.text
Additional model comparison plots, for Xpose 4add.model.comp
Additional goodness-of-fit plots, for Xpose 4addit.gof
Autocorrelation of conditional weighted residuals for Xpose 4autocorr.cwres
autocorrelation of the individual weighted residualsautocorr.iwres
Autocorrelation of weighted residuals for Xpose 4autocorr.wres
Basic goodness-of-fit plots, for Xpose 4basic.gof
Basic model comparison plots, for Xpose 4basic.model.comp
Function to create histograms of results from the 'bootstrap' tool in PsNboot.hist
Print summary information for a bootgam or bootscmbootgam.print
Import bootscm data into R/Xposebootscm.import
Categorical observations vs. independent variable using stacked bars.cat.dv.vs.idv.sb
Categorical (visual) predictive check.cat.pc
Functions changing variable definitions in Xpose 4change.ab.graph.par change.bw.graph.par change.cond.graph.par change.dil.graph.par change.label.par change.lm.graph.par change.misc.graph.par change.pi.graph.par change.smooth.graph.par change_graphical_parameters
Functions changing miscellaneous parameter settings in Xpose 4change.cat.cont change.cat.cont<- change.cat.levels change.cat.levels<- change.dv.cat.levels change.dv.cat.levels<- change.miss change.subset change_misc_parameters get.doc set.doc
Change parameter scope.change.parm
Changes the name of an Xpose data itemchange.var.name
Changes the label of an Xpose data itemchange.xlabel
Change Xpose variable definitions.change.xvardef change.xvardef<-
Compute the Conditional Weighted Residualscompute.cwres ind.cwres is.cwres.readable.file read.cwres.data sqrtm xpose.calculate.cwres
Plot scatterplot matrices of parameters, random parameters or covariatescov.splom parm.splom par_cov_splom ranpar.splom
Create xpose.multiple.plot class.create.xpose.plot.classes print,xpose.multiple.plot-method
This function creates the Xpose data classes ("xpose.data" and "xpose.prefs")createXposeClasses
Histogram of conditional weighted residuals (CWRES), for Xpose 4cwres.dist.hist
Quantile-quantile plot of conditional weighted residuals (CWRES), for Xpose 4cwres.dist.qq
Conditional Weighted residuals (CWRES) plotted against covariates, for Xpose 4cwres.vs.cov
Population conditional weighted residuals (CWRES) plotted against the independent variable (IDV) for Xpose 4cwres.vs.idv
Box-and-whisker plot of conditional weighted residuals vs the independent variable for Xpose 4cwres.vs.idv.bw
Population conditional weighted residuals (CWRES) plotted against population predictions (PRED) for Xpose 4cwres.vs.pred
Box-and-whisker plot of conditional weighted residuals vs population predictions for Xpose 4cwres.vs.pred.bw
Weighted residuals (WRES) and conditional WRES (CWRES) plotted against the independent variable (IDV)cwres.wres.vs.idv
Weighted residuals (WRES) and conditional WRES (CWRES) plotted against the population predictions (PRED)cwres.wres.vs.pred
Extract or assign data from an xpose.data object.Data Data<- data_extract_or_assign SData SData<-
Check through the source dataset to detect problemsdata.checkout
Prints the contents of an Xpose data objectdb.names
Change in individual objective function value vs. covariate value.dOFV.vs.cov
Change in Objective function value vs. removal of individuals.dOFV.vs.id
Change in individual objective function value 1 vs. individual objective function value 2.dOFV1.vs.dOFV2
Observations (DV), individual predictions (IPRED) and population predictions (IPRED) plotted against the independent variable (IDV), for Xpose 4dv.preds.vs.idv
Observations (DV) plotted against the independent variable (IDV) for Xpose 4dv.vs.idv
Observations (DV) plotted against individual predictions (IPRED) for Xpose 4dv.vs.ipred
Dependent variable vs individual predictions, conditioned on covariates, for Xpose 4dv.vs.ipred.by.cov
Dependent variable vs individual predictions, conditioned on independent variable, for Xpose 4dv.vs.ipred.by.idv
Observations (DV) plotted against population predictions (PRED) for Xpose 4dv.vs.pred
Dependent variable vs population predictions, conditioned on covariates, for Xpose 4dv.vs.pred.by.cov
Dependent variable vs population predictions, conditioned on independent variable, for Xpose 4dv.vs.pred.by.idv
Observations (DV) are plotted against individual predictions (IPRED) and population predictions (PRED), for Xpose 4dv.vs.pred.ipred
Exports Xpose graphics settings to a file.export.graph.par xpose.write
Exports Xpose variable definitions to a file from an Xpose data object.export.variable.definitions
GAM functions for Xpose 4GAM_summary_and_plot xp.akaike.plot xp.cook xp.ind.inf.fit xp.ind.inf.terms xp.ind.stud.res xp.plot xp.summary
Structured goodness of fit diagnostics.gof gofSetup xpPage
Imports Xpose graphics settings from a file to an Xpose data object.import.graph.par xpose.read
Imports Xpose variable definitions from a file to an Xpose data object.import.variable.definitions
Observations (DV), individual predictions (IPRED) and population predictions (PRED) are plotted against the independent variable for every individual in the dataset, for Xpose 4ind.plots
Histograms of weighted residuals for each individual in an Xpose data object, for Xpose 4ind.plots.cwres.hist ind.plots.wres.hist
Quantile-quantile plots of weighted residuals for each individual in an Xpose data object, for Xpose 4ind.plots.cwres.qq ind.plots.wres.qq
Individual predictions (IPRED) plotted against the independent variable (IDV) for Xpose 4ipred.vs.idv
Histogram of individual weighted residuals (IWRES), for Xpose 4iwres.dist.hist
Quantile-quantile plot of individual weighted residuals (IWRES), for Xpose 4iwres.dist.qq
Individual weighted residuals (IWRES) plotted against the independent variable (IDV) for Xpose 4iwres.vs.idv
Kaplan-Meier plots of (repeated) time-to-event datakaplan.plot
Make stacked bar data set.make.sb.data
Function to plot the coverage of the Numerical Predictive Checknpc.coverage
Extract or set the value of the Nsim slot.nsim nsim<-
Plot the parameter or covariate distributions using a histogramcov.hist parm.hist par_cov_hist ranpar.hist
Plot the parameter or covariate distributions using quantile-quantile (Q-Q) plotscov.qq parm.qq par_cov_qq ranpar.qq
Summarize individual parameter values and covariatescov.summary parm.summary par_cov_summary
Parameters plotted against covariates, for Xpose 4parm.vs.cov
Plot parameters vs other parametersparm.vs.parm
Population predictions (PRED) plotted against the independent variable (IDV) for Xpose 4pred.vs.idv
Print an Xpose multiple plot object.print.xpose.multiple.plot
Function to create a histogram of results from the randomization test tool ('randtest') in PsNrandtest.hist
Random parameters plotted against covariates, for Xpose 4ranpar.vs.cov
Read NONMEM output files into Xpose 4calc.npar create.parameter.list read.lst read_NM_output
Read NONMEM table files produced from simulation.read_nm_table
Reading NONMEM table filesread.nm.tables
Read the results file from a Numerical or Visual Predictive Check run in PsNread.npc.vpc.results
Read (repeated) time-to-event simulation data files.read.TTE.sim.data
Read the vpctab file from PsN into Xposeread.vpctab
Resets Xpose variable definitions to factory settingsreset.graph.par
Print run summary in Xpose 4runsum
Simulated prazosin Xpose database.simpraz.xpdb
Function to create files for the simulated prazosin example in XposesimprazExample
Tabulate the population parameter estimatestabulate.parameters
Histogram of weighted residuals (WRES), for Xpose 4wres.dist.hist
Quantile-quantile plot of weighted residuals (WRES), for Xpose 4wres.dist.qq
Weighted residuals (WRES) plotted against covariates, for Xpose 4wres.vs.cov
Population weighted residuals (WRES) plotted against the independent variable (IDV) for Xpose 4wres.vs.idv
Box-and-whisker plot of weighted residuals vs the independent variable for Xpose 4wres.vs.idv.bw
Population weighted residuals (WRES) plotted against population predictions (PRED) for Xpose 4wres.vs.pred
Box-and-whisker plot of weighted residuals vs population predictions for Xpose 4wres.vs.pred.bw
Extract and set labels for Xpose data items.xlabel xlabel<-
Compare parameter estimates for covariate coefficientsxp.boot.par.est
Correlations between covariate coefficientsxp.boot.par.est.corr
Distribution of difference in AICxp.daic.npar.plot
Plot of model size distribution for a bootgam or bootscmxp.distr.mod.size
Distribution of difference in OFVxp.dofv.npar.plot
OFV difference (optimism) plot.xp.dofv.plot
Default function for calculating dispersion in 'xpose.gam'.xp.get.disp
Trace plots for conditional indicesxp.inc.cond.stab.cov
Trace plots for conditional indices rper replicate numberxp.inc.ind.cond.stab.cov
Inclusion frequency plotxp.inc.prob
Inclusion frequency plot for combination of covariates.xp.inc.prob.comb.2
Inclusion stability plot A plot of the inclusion frequency of covariates vs bootgam/bootscm iteration number. This plot can be used to evaluate whether sufficient iterations have been performed.xp.inc.stab.cov
Plot of inclusion index of covariates.xp.incl.index.cov
Inclusion index individuals, compare between covariates.xp.incl.index.cov.comp
Individual inclusion indexxp.incl.index.cov.ind
Define a scope for the gam. Used as default input to the 'scope' argument in 'xpose.gam'xp.scope3
Titlexpose.bootgam
Create an Xpose data objectxpose.data
Class xpose.datadata.frame_or_NULL-class numeric_or_NULL-class xpose.data-class
Stepwise GAM search for covariates on a parameter (Xpose 4)xpose.gam
Displays the Xpose license and citation informationxpose.license.citation
Functions to create nice looking axes when using Log scales.xpose.logTicks xpose.xscale.components.log10 xpose.yscale.components.log10
Create and object with class "xpose.multiple.plot".xpose.multiple.plot
Class for creating multiple plots in xposecharacter_or_NULL-class list_or_NULL-class logical_or_numeric-class xpose.multiple.plot-class
Xpose 4 generic function for plotting multiple lattice objects on one pagexpose.multiple.plot.default
Default box-and-whisker panel function for Xpose 4xpose.panel.bw
Default panel function for Xpose 4xpose.panel.default
Default histogram panel function for Xpose 4xpose.panel.histogram
Default QQ panel function for Xpose 4xpose.panel.qq
Scatterplot matrix panel function for Xpose 4xpose.panel.splom
The generic Xpose functions for box-and-whisker plotsxpose.plot.bw
The Xpose 4 generic functions for continuous y-variables.xpose.plot.default
The Xpose 4 generic functions for continuous y-variables.xpose.plot.histogram
The generic Xpose functions for QQ plotsxpose.plot.qq
The Xpose 4 generic functions for scatterplot matrices.xpose.plot.splom
Class "xpose.prefs"character_or_numeric-class xpose.prefs-class
Summarize an xpose databasexpose.print
Print a pretty string.xpose.string.print
Visual Predictive Check (VPC) using XPOSExpose.VPC
Xpose Visual Predictive Check (VPC) for both continuous and Limit of Quantification data.xpose.VPC.both
Xpose visual predictive check for categorical data.xpose.VPC.categorical
Classic menu system for Xpose 4xpose4
Extract or set the value of the Subset slot.xsubset xsubset<-
Extract and set Xpose variable definitions.xvardef xvardef<-