bin.time: Bin time-concentration data using quantile or algorithmic...

In nlmixr2autoinit: Automatic Generation of Initial Estimates for Population Pharmacokinetic Modeling

Bin time-concentration data using quantile or algorithmic binning

Description

Bins data by time using either equal-frequency (quantile) binning or algorithmic binning methods.

Usage

bin.time(
  dat,
  nbins = "auto",
  bin.method = c("quantile", "jenks", "kmeans", "pretty", "sd", "equal", "density")
)

Arguments

dat	A data frame containing PK data. Must include: tad: time after dose DVstd: standardized concentration (DV/dose) EVID: optional event ID column used to filter observations (EVID == 0)
nbins	Number of bins or "auto". If numeric with bin.method = "quantile", specifies equal-frequency bins. If "auto", 10 bins are used for quantile; otherwise binning is determined by vpc::auto_bin. Numeric nbins for non-quantile methods is passed to vpc::auto_bin.
bin.method	Binning strategy (default = "quantile"). Available options are: quantile: equal-frequency binning by empirical quantiles jenks: natural breaks minimizing within-bin variance kmeans, pretty, sd, equal, density: alternative binning methods from vpc::auto_bin

Details

Supports quantile-based binning and other data-driven methods (jenks, kmeans, pretty, sd, equal, density), with optional automatic bin count selection.

Value

A list containing summary results of the time-concentration binning process.

Author(s)

Zhonghui Huang

See Also

vpc::auto_bin

Examples

dat <- Bolus_1CPT
dat <- nmpkconvert(dat)
dat <- calculate_tad(dat)
dat$DVstd <- dat$DV / dat$dose
bin.time(dat)

nlmixr2autoinit documentation built on Nov. 14, 2025, 1:07 a.m.