getTimeChoicePerformance: estimate the distance between population average an average...

In microsamplingDesign: Finding Optimal Microsampling Designs for Non-Compartmental Pharmacokinetic Analysis

Description

estimate the distance between population average an average over sample datasets with given time points (zero point included)

Usage

getTimeChoicePerformance(timePointInd, pkData, popAvCurve, timeGrid,
  printMCError = FALSE)

Arguments

timePointInd	a vector indicating time points indicator selection of time points from fullTimePoints
pkData	PkData-class
popAvCurve	an interpolated population average curve
timeGrid	the grid point at which to interpolate the curve
printMCError	logical indicater when true the MC error is printed to the terminal, defaults to FALSE

Value

numeric value of the timePoint choice performance

Examples

 # get example inputs
 fullPkData                 <-  getExampleTimeData() # PkData object
 fullTimePoints             <-  getTimePoints(fullPkData)
 examplePopAvCurve          <-  fullTimePoints^2 
 timePointIndicators        <-  c( 1 , 5, 21 ) # zero point included
 nGridPoints                <-  25
 timeGrid                   <-  seq( min( fullTimePoints ),
    max( fullTimePoints ) , length.out = nGridPoints ) 
 popCurveInterpolated       <-  microsamplingDesign:::interpolateVec( fullTimePoints ,
   examplePopAvCurve,  timeGrid )

 getTimeChoicePerformance( timePointInd = timePointIndicators, pkData = fullPkData ,
   popAvCurve = popCurveInterpolated, timeGrid ) 

 getTimeChoicePerformance( timePointInd = timePointIndicators, pkData = fullPkData ,
   popAvCurve = popCurveInterpolated, timeGrid, printMCError = TRUE ) 

microsamplingDesign documentation built on Oct. 13, 2021, 5:10 p.m.