VPC: Visual predictive checks

In saviclab/savictools: Streamlined Data Manipulation for Pharmacometrics

Visual predictive checks

Description

VPC() allows you to run PsN's vpc command and generate a visual predictive check with xpose4::xpose.VPC() in one line of code in the R console.

Usage

VPC(runno, psn_args = NULL, overwrite = FALSE, ...)

Arguments

runno	A run number or model name.
psn_args	Optional. A character string containing arguments to PsN's vpc program.
overwrite	Optional. Logical. Should VPC() run a new VPC, deleting old VPC directories?
...	Optional. Additional arguments to xpose4::xpose.VPC().

Details

Let the name of your model for VPC be called "runXX.mod". runXX.mod must exist in your current working directory. If a vpc_runXX directory already exists from a previous VPC, and overwrite = FALSE, psn_args can be left blank, and you need only supply the run number/model name.

Value

No return value, called for side effects

Author(s)

Sandy Floren

Examples

## Not run: 
# run VPC for run46.mod using runno = 46
VPC(46, "-samples=500 -bin_array=-0.5,0.5,1.5,2.5,3.5,5,7,11,13,24.5
-idv=TAD -bin_by_count=0", subset = "TAD <= 24")

# run VPC for run46.mod using runno = "run46"
VPC("run46", "-samples=500 -bin_array=-0.5,0.5,1.5,2.5,3.5,5,7,11,13,24.5
-idv=TAD -bin_by_count=0", subset = "TAD <= 24")


## End(Not run)

saviclab/savictools documentation built on Dec. 7, 2023, 11:56 p.m.