vpc_nlmixr_nlme: Visual predictive check (VPC) for nlmixr nlme objects

In nlmixr: Nonlinear Mixed Effects Models in Population PK/PD

Visual predictive check (VPC) for nlmixr nlme objects

Description

Do visual predictive check (VPC) plots for nlme-based non-linear mixed effect models

Usage

vpc_nlmixr_nlme(fit, nsim = 100, condition = NULL, ...)

vpcNlmixrNlme(fit, nsim = 100, condition = NULL, ...)

## S3 method for class 'nlmixrNlme'
vpc(sim, ...)

Arguments

fit	nlme fit object
nsim	number of simulations
condition	conditional variable
...	Additional 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

Value

Called for its side effects of creating a VPC

Examples

specs <- list(fixed=lKA+lCL+lV~1, random = pdDiag(lKA+lCL~1), start=c(lKA=0.5, lCL=-3.2, lV=-1))
fit <- nlme_lin_cmpt(theo_md, par_model=specs, ncmt=1, verbose=TRUE)
vpc_nlmixr_nlme(fit, nsim = 100, condition = NULL)

nlmixr documentation built on March 27, 2022, 5:05 p.m.