eval_perf_1cmpt: Evaluates predictive performance of a one-compartment model

Description

Computes predictive error metrics by comparing simulated and observed concentration–time data using specified pharmacokinetic parameters and dosing route.

Usage

eval_perf_1cmpt(
  dat,
  est.method = "rxSolve",
  ka = NULL,
  cl = NULL,
  vd = NULL,
  route = c("bolus", "infusion", "oral")
)

Value

A numeric vector containing absolute prediction error, mean absolute error, mean absolute percentage error, root mean square error, and relative root mean square error.

Arguments

dat: A data frame containing raw time–concentration data in the standard nlmixr2 format.
est.method: Estimation method passed to the fitting function. Defaults to using rxSolve for model simulation and parameter estimation.
ka: Absorption rate constant.
cl: Clearance value.
vd: Volume of distribution.
route: A character string indicating the route of administration. Must be one of "oral", "infusion", or "bolus". Defaults to "bolus".

Details

Internally selects the appropriate one-compartment model fitting function, using Fit_1cmpt_oral() for oral administration and Fit_1cmpt_iv() for intravenous administration. Predictive performance is quantified using the metrics.() function.

Examples

Run this code


eval_perf_1cmpt(
  dat = Oral_1CPT,
  est.method = "rxSolve",
  ka = 1,
  cl = 4,
  vd = 70,
  route = "oral"
)