Reference

Model Building

Built-in Models

Use these functions to define various types of PK/PD models.

pkmodel()

Creates a PK model

pklinearmodel()

Create PK linear model

pkemaxmodel()

Create a PK/Emax or PK/Imax model

pkindirectmodel()

Create a PK/Indirect response model

emaxmodel()

Create an Emax or Imax model

linearmodel()

Create linear model

Add/Edit Model Parameters

Use these functions to add/update model parameters.

addCovariate()

Add covariate to model object

removeCovariate()

Remove covariate from structural parameters in a model object.

fixedEffect()

Specifies the initial values, lower bounds, upper bounds, and units for fixed effects in a model

randomEffect()

Sets or updates the covariance matrix of random effects

structuralParameter()

Set structural parameter in model object

addSecondary()

Adds a secondary parameter to model definition

Edit Residual Error Models

residualError()

Assign residual error model to model object

Textual Models

Use these functions to create and update a textual model object.

textualmodel()

Create a textual model object

addLabel()

Add levels and labels to categorical or occasion covariate

addInfusion()

Change existing dosing compartment to infusion

Edit and Copy Models

Use these functions to edit and copy a model object.

editModel()

Directly edit PML text in model object

copyModel()

Copy model object to iterate over base model

Initial Estimates

Shiny application used to set and visualize initial estimates.

estimatesUI()

Shiny GUI to examine the model and evaluate estimates for fixed effects

Column Mapping

Use these functions to associate model variables with input data columns and to add extra mapping information to the column definition file.

dataMapping()

Initialize input data for PK/PD model

colMapping()

Add column mappings

addExtraDef()

Adds user defined extra column/table definitions to column definition file

addADDL()

Adds ADDL extra column definition to model object

addSteadyState()

Adds Steady State extra column definition to model object

addDoseCycle()

Adds a dosing cycle to model

addMDV()

Adds MDV extra column definition to model object

addReset()

Adds reset instructions to the model

Model Execution

Use these functions to perform various types of model execution.

fitmodel()

Executes an NLME simple estimation

sortfit()

Executes an NLME simple estimation with sort keys and given scenarios

stepwiseSearch()

Executes an NLME stepwise covariate search

shotgunSearch()

Executes an NLME shotgun covariate search

bootstrap()

Executes an NLME Bootstrap

vpcmodel()

Perform visual predictive check for NLME models

simmodel()

Executes an NLME simulation

engineParams()

Specify engine parameters for model execution

hostParams()

Initialize for NlmeParallelHost

tableParams()

Wrapper around NlmeTableDef/NlmeSimTableDef-classes initializers.

Model Information

Use these functions to return useful model information.

modelVariableNames()

Return model variable names

modelRandParamsMapping()

Lists mapping between model random effects and input columns

residualEffectNames()

Return residual effect terms available in model

covariateNames()

Return covariate names

doseNames()

Return dose names

listCovariateEffectNames()

Lists covariate effect names in the model

listSecondary()

Lists secondary parameter definitions for the model

secondaryParameterNames()

Get secondary parameter names

structuralParameterNames()

Get structural parameter names

getThetas()

Return theta names and values

Built-in Data

Built-in datasets.

pkData

Pharmacokinetic dataset containing 16 subjects with single bolus dose

pkpdData

Pharmacokinetic/Pharmacodynamic dataset containing 200 subjects with single bolus dose

pkcovbqlData

Pharmacokinetic pediatric dataset containing 80 subjects with single bolus dose.

OneCpt_IVInfusionData

Pharmacokinetic dataset containing 100 subjects with single dose given by infusion