calc_vpc_continuous: Calculate aggregate statistics for simulated and observed VPC...

In ronkeizer/vpc: Create Visual Predictive Checks

Calculate aggregate statistics for simulated and observed VPC data

Description

Calculate aggregate statistics for simulated and observed VPC data

Usage

calc_vpc_continuous(sim, obs, loq, pi, ci, stratify, bins, bin_mid, verbose)

Arguments

sim	this is usually a data.frame with observed data, containing the independent and dependent variable, a column indicating the individual, and possibly covariates. E.g. load in from NONMEM using read_table_nm. However it can also be an object like a nlmixr or xpose object
obs	a data.frame with observed data, containing the independent and dependent variable, a column indicating the individual, and possibly covariates. E.g. load in from NONMEM using read_table_nm
loq	The list output from define_loq()
pi	simulated prediction interval to plot. Default is c(0.05, 0.95),
ci	confidence interval to plot. Default is (0.05, 0.95)
stratify	character vector of stratification variables.
bins	either "density", "time", or "data", "none", or one of the approaches available in classInterval() such as "jenks" (default) or "pretty", or a numeric vector specifying the bin separators.
bin_mid	either "mean" for the mean of all timepoints (default) or "middle" to use the average of the bin boundaries.
verbose	show debugging information (TRUE or FALSE)

Value

A list with "vpc_dat" and "aggr_obs"

ronkeizer/vpc documentation built on May 11, 2023, 11:09 p.m.