{
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  "Package": "nlmixr2extra",
  "Title": "Nonlinear Mixed Effects Models in Population PK/PD, Extra\nSupport Functions",
  "Version": "5.1.0",
  "Authors@R": "c(\nperson(\"Matthew\", \"Fidler\", email=\"matthew.fidler@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0001-8538-6691\")),\nperson(\"Vipul\", \"Mann\",email=\"vm2583@columbia.edu\", role = \"aut\"),\nperson(\"Vishal\", \"Sarsani\", email=\"vsarsani@umass.edu\", comment=c(ORCID = \"0000-0002-9272-3438\"), role=\"aut\"),\nperson(\"Christian\", \"Bartels\", email=\"christian.bartels@novartis.com\", role=\"ctb\"),\nperson(\"Bill\", \"Denney\", email=\"wdenney@humanpredictions.com\", role=\"aut\", comment=c(ORCID=\"0000-0002-5759-428X\")),\nperson(\"Omar\", \"Elashkar\", email=\"omar.i.elashkar@gmail.com\", role=\"ctb\", comment=c(ORCID=\"0000-0002-5505-778X\"))\n)",
  "Maintainer": "Matthew Fidler <matthew.fidler@gmail.com>",
  "Description": "Fit and compare nonlinear mixed-effects models in\ndifferential equations with flexible dosing information\ncommonly seen in pharmacokinetics and pharmacodynamics\n(Almquist, Leander, and Jirstrand 2015\n<doi:10.1007/s10928-015-9409-1>). Differential equation solving\nis by compiled C code provided in the 'rxode2' package (Wang,\nHallow, and James 2015 <doi:10.1002/psp4.12052>). This package\nis for support functions like preconditioned fits\n<doi:10.1208/s12248-016-9866-5>, boostrap and stepwise\ncovariate selection.",
  "License": "GPL (>= 3)",
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  "BugReports": "https://github.com/nlmixr2/nlmixr2extra/issues/",
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  "Repository": "https://nlmixr2.r-universe.dev",
  "Date/Publication": "2026-06-05 15:46:27 UTC",
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  "Author": "Matthew Fidler [aut, cre] (ORCID:\n<https://orcid.org/0000-0001-8538-6691>),\nVipul Mann [aut],\nVishal Sarsani [aut] (ORCID: <https://orcid.org/0000-0002-9272-3438>),\nChristian Bartels [ctb],\nBill Denney [aut] (ORCID: <https://orcid.org/0000-0002-5759-428X>),\nOmar Elashkar [ctb] (ORCID: <https://orcid.org/0000-0002-5505-778X>)",
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    "adaptivelassoCoefficients",
    "addAllEtas",
    "addCatCovariates",
    "addCovariate",
    "addData2Rx",
    "addorremoveCovariate",
    "adjustedlassoCoefficients",
    "bootplot",
    "bootstrapFit",
    "buildcovInfo",
    "buildupatedUI",
    "covarSearchAuto",
    "fixedControl",
    "foldgen",
    "horseshoeSummardf",
    "iivSearch",
    "ini",
    "isLinearizeMatch",
    "knit_print",
    "lassoCoefficients",
    "lassoSummardf",
    "linearize",
    "linearizeErrorLines",
    "linearizePlot",
    "linModGen",
    "llpControl",
    "model",
    "nlmixr",
    "nlmixr2",
    "nlmixrFormula",
    "nlmixrWithTiming",
    "normalizedData",
    "optimUnisampling",
    "preconditionFit",
    "profileFixed",
    "profileFixedSingle",
    "profileLlp",
    "regularmodel",
    "rerunTopN",
    "resSearch",
    "rxUiDeparse"
  ],
  "_datasets": [
    {
      "name": "theoFitOde",
      "title": "Example single dose Theophylline ODE model",
      "object": "theoFitOde",
      "class": [
        "nlmixr2FitData",
        "nlmixr2FitCore",
        "nlmixr2.focei",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
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        "ID",
        "TIME",
        "DV",
        "PRED",
        "RES",
        "WRES",
        "IPRED",
        "IRES",
        "IWRES",
        "CPRED",
        "CRES",
        "CWRES",
        "eta.ka",
        "eta.cl",
        "eta.v",
        "depot",
        "center",
        "ka",
        "cl",
        "v",
        "tad",
        "dosenum"
      ],
      "rows": 132,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "dot-nlmixrFormulaDataPrep",
      "title": "Perform any required data modifications for the nlmixrFormula interface",
      "topics": [
        ".nlmixrFormulaDataPrep"
      ]
    },
    {
      "page": "dot-nlmixrFormulaExpandStartParam",
      "title": "Expand parameters to include their covariate representations, if applicable.",
      "topics": [
        ".nlmixrFormulaExpandStartParam",
        ".nlmixrFormulaExpandStartParamSingle"
      ]
    },
    {
      "page": "dot-nlmixrFormulaParser",
      "title": "Parse the formula to extract the dependent variable, predictor, and random effects",
      "topics": [
        ".nlmixrFormulaParser"
      ]
    },
    {
      "page": "dot-nlmixrFormulaParserRanef",
      "title": "Parse the random effects part of a formula",
      "topics": [
        ".nlmixrFormulaParserRanef"
      ]
    },
    {
      "page": "dot-nlmixrFormulaSetupIniFixed",
      "title": "Setup the ini() part of the model for fixed effects",
      "topics": [
        ".nlmixrFormulaSetupIniFixed",
        ".nlmixrFormulaSetupIniRandom"
      ]
    },
    {
      "page": "dot-renameOrOverwrite",
      "title": "Rename a column in a dataset",
      "topics": [
        ".renameOrOverwrite"
      ]
    },
    {
      "page": "aaaNlmixr2ExtraCRAN",
      "title": "This function is to set the number of threads to 2",
      "topics": [
        "aaaNlmixr2ExtraCRAN"
      ]
    },
    {
      "page": "adaptivelassoCoefficients",
      "title": "Return Adaptive lasso coefficients after finding optimal t",
      "topics": [
        "adaptivelassoCoefficients"
      ]
    },
    {
      "page": "addAllEtas",
      "title": "Add Individual Random Effects and Fix them to Small Value",
      "topics": [
        "addAllEtas"
      ]
    },
    {
      "page": "addCatCovariates",
      "title": "Make dummy variable cols and updated covarsVec",
      "topics": [
        "addCatCovariates"
      ]
    },
    {
      "page": "addCovariate",
      "title": "Add Covariate to Model Fit (Generic)",
      "topics": [
        "addCovariate",
        "addCovariate.default",
        "addCovariate.nlmixr2FitCore",
        "addCovariate.nlmixr2Linearize",
        "addCovariate.rxUi"
      ]
    },
    {
      "page": "addData2Rx",
      "title": "Add Data to RxUi model",
      "topics": [
        "addData2Rx"
      ]
    },
    {
      "page": "addorremoveCovariate",
      "title": "Add covariate",
      "topics": [
        "addorremoveCovariate"
      ]
    },
    {
      "page": "adjustedlassoCoefficients",
      "title": "Return Adjusted adaptive lasso coefficients after finding optimal t",
      "topics": [
        "adjustedlassoCoefficients"
      ]
    },
    {
      "page": "bootplot",
      "title": "Produce delta objective function for boostrap",
      "topics": [
        "bootplot",
        "bootplot.nlmixr2FitCore"
      ]
    },
    {
      "page": "bootstrapFit",
      "title": "Bootstrap nlmixr2 fit",
      "topics": [
        "bootstrapFit"
      ]
    },
    {
      "page": "buildcovInfo",
      "title": "Build covInfo list from varsVec and covarsVec",
      "topics": [
        "buildcovInfo"
      ]
    },
    {
      "page": "buildupatedUI",
      "title": "Build updated from the covariate and variable vector list",
      "topics": [
        "buildupatedUI"
      ]
    },
    {
      "page": "covarSearchAuto",
      "title": "Stepwise Covariate Model-selection (SCM) method",
      "topics": [
        "covarSearchAuto"
      ]
    },
    {
      "page": "fixedControl",
      "title": "Control options for fixed-value likelihood profiling",
      "concept": [
        "Profiling"
      ],
      "topics": [
        "fixedControl"
      ]
    },
    {
      "page": "foldgen",
      "title": "Stratified cross-validation fold generator function, inspired from the caret",
      "topics": [
        "foldgen"
      ]
    },
    {
      "page": "horseshoeSummardf",
      "title": "Create Horseshoe summary posterior estimates",
      "topics": [
        "horseshoeSummardf"
      ]
    },
    {
      "page": "iivSearch",
      "title": "Automated Inter-Individual Variability Search",
      "topics": [
        "iivSearch",
        "iivSearch.default",
        "iivSearch.nlmixr2Linearize"
      ]
    },
    {
      "page": "isLinearizeMatch",
      "title": "Check Linearization Match",
      "topics": [
        "isLinearizeMatch"
      ]
    },
    {
      "page": "knit_print.nlmixr2FitCore",
      "title": "Extract the equations from an nlmixr2/rxode2 model to produce a 'LaTeX' equation.",
      "topics": [
        "knit_print.nlmixr2FitCore",
        "knit_print.rxUi"
      ]
    },
    {
      "page": "lassoCoefficients",
      "title": "Return Final lasso coefficients after finding optimal t",
      "topics": [
        "lassoCoefficients"
      ]
    },
    {
      "page": "lassoSummardf",
      "title": "Create Lasso summary posterior estimates",
      "topics": [
        "lassoSummardf"
      ]
    },
    {
      "page": "linearize",
      "title": "Perform linearization of a model fitted using FOCEI",
      "topics": [
        "linearize"
      ]
    },
    {
      "page": "linearizePlot",
      "title": "Plot Original Versus Linear Models iObj and Etas",
      "topics": [
        "linearizePlot"
      ]
    },
    {
      "page": "linModGen",
      "title": "Generate a Linearization Model From Previous Fit",
      "topics": [
        "linModGen"
      ]
    },
    {
      "page": "llpControl",
      "title": "Control options for log-likelihood profiling",
      "concept": [
        "Profiling"
      ],
      "topics": [
        "llpControl"
      ]
    },
    {
      "page": "nlmixrFormula",
      "title": "A simple formula-based interface for nlmixr2",
      "topics": [
        "nlmixrFormula"
      ]
    },
    {
      "page": "normalizedData",
      "title": "Function to return data of normalized covariates",
      "topics": [
        "normalizedData"
      ]
    },
    {
      "page": "optimUnisampling",
      "title": "Sample from uniform distribution by optim",
      "topics": [
        "optimUnisampling"
      ]
    },
    {
      "page": "preconditionFit",
      "title": "Linearly re-parameterize the model to be less sensitive to rounding errors",
      "topics": [
        "preconditionFit"
      ]
    },
    {
      "page": "print.linIIVSearch",
      "title": "Print Summary Table For Linearized IIV Search",
      "topics": [
        "print.linIIVSearch"
      ]
    },
    {
      "page": "profile.nlmixr2FitCore",
      "title": "Perform likelihood profiling on nlmixr2 focei fits",
      "concept": [
        "Profiling"
      ],
      "topics": [
        "profile.nlmixr2FitCore"
      ]
    },
    {
      "page": "profileFixed",
      "title": "Estimate the objective function values for a model while fixing defined parameter values",
      "concept": [
        "Profiling"
      ],
      "topics": [
        "profileFixed",
        "profileFixedSingle"
      ]
    },
    {
      "page": "profileLlp",
      "title": "Profile confidence intervals with log-likelihood profiling",
      "concept": [
        "Profiling"
      ],
      "topics": [
        "profileLlp"
      ]
    },
    {
      "page": "profileNlmixr2FitCoreRet",
      "title": "Give the output data.frame for a single model for profile.nlmixr2FitCore",
      "concept": [
        "Profiling"
      ],
      "topics": [
        "profileNlmixr2FitCoreRet"
      ]
    },
    {
      "page": "regularmodel",
      "title": "Regular lasso model",
      "topics": [
        "regularmodel"
      ]
    },
    {
      "page": "rerunTopN",
      "title": "Rerun Top N Original Models From A Search",
      "topics": [
        "rerunTopN",
        "rerunTopN.linIIVSearch"
      ]
    },
    {
      "page": "resSearch",
      "title": "Exhaustively Search for Residual Error Model",
      "topics": [
        "resSearch"
      ]
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