Model Building |
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Built-in ModelsUse these functions to define various types of PK/PD models. |
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Creates a PK model |
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Create PK linear model |
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Create a PK/Emax or PK/Imax model |
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Create a PK/Indirect response model |
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Create an Emax or Imax model |
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Create linear model |
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Add/Edit Model ParametersUse these functions to add/update model parameters. |
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Add covariate to model object |
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Remove covariate from structural parameters in a model object. |
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Specifies the initial values, lower bounds, upper bounds, and units for fixed effects in a model |
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Sets or updates the covariance matrix of random effects |
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Set structural parameter in model object |
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Adds a secondary parameter to model definition |
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Edit Residual Error Models |
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Assign residual error model to model object |
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Textual ModelsUse these functions to create and update a textual model object. |
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Create a textual model object |
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Add levels and labels to categorical or occasion covariate |
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Change existing dosing compartment to infusion |
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Edit and Copy ModelsUse these functions to edit and copy a model object. |
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Directly edit PML text in model object |
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Copy model object to iterate over base model |
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Initial EstimatesShiny application used to set and visualize initial estimates. |
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Shiny GUI to examine the model and evaluate estimates for fixed effects |
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Column MappingUse these functions to associate model variables with input data columns and to add extra mapping information to the column definition file. |
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Initialize input data for PK/PD model |
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Add column mappings |
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Adds user defined extra column/table definitions to column definition file |
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Adds ADDL extra column definition to model object |
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Adds Steady State extra column definition to model object |
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Adds a dosing cycle to model |
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Adds MDV extra column definition to model object |
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Adds reset instructions to the model |
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Model ExecutionUse these functions to perform various types of model execution. |
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Executes an NLME simple estimation |
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Executes an NLME simple estimation with sort keys and given scenarios |
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Executes an NLME stepwise covariate search |
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Executes an NLME shotgun covariate search |
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Executes an NLME Bootstrap |
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Perform visual predictive check for NLME models |
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Executes an NLME simulation |
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Specify engine parameters for model execution |
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Initialize for NlmeParallelHost |
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Wrapper around NlmeTableDef/NlmeSimTableDef-classes initializers. |
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Model InformationUse these functions to return useful model information. |
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Return model variable names |
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Lists mapping between model random effects and input columns |
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Return residual effect terms available in model |
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Return covariate names |
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Return dose names |
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Lists covariate effect names in the model |
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Lists secondary parameter definitions for the model |
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Get secondary parameter names |
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Get structural parameter names |
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Return theta names and values |
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Built-in DataBuilt-in datasets. |
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Pharmacokinetic dataset containing 16 subjects with single bolus dose |
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Pharmacokinetic/Pharmacodynamic dataset containing 200 subjects with single bolus dose |
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Pharmacokinetic pediatric dataset containing 80 subjects with single bolus dose. |
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Pharmacokinetic dataset containing 100 subjects with single dose given by infusion |