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vpc (version 1.2.4)

Create Visual Predictive Checks

Description

Visual predictive checks are a commonly used diagnostic plot in pharmacometrics, showing how certain statistics (percentiles) for observed data compare to those same statistics for data simulated from a model. The package can generate VPCs for continuous, categorical, censored, and (repeated) time-to-event data.

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Install

install.packages('vpc')

Monthly Downloads

1,455

Version

1.2.4

License

MIT + file LICENSE

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Repository

https://github.com/ronkeizer/vpc

Maintainer

Ron Keizer

Last Published

February 17th, 2026

Functions in vpc (1.2.4)

Calculate quantiles respecting the censored data

ggplot2_label_variable

Function copied from ggplot2:::label_variable, with addition of ` Copied here since CRAN does not like use of `:::`.

ggplot.vpcdb_continuous

Create a ggplot for each vpcdb type

calc_vpc_continuous

Calculate aggregate statistics for simulated and observed VPC data

Simulate PK data from a 1-compartment oral model

VPC plotting function

Add noise / residual error to data

plot_vpc_helper

Helper function to simplify vpc plotting (not intended to be called directly)

add_sim_index_number

Add sim index number

Calculate fraction of observations below lloq / above uloq

Custom ggplot2 labeller function.

Defaults for show argument with various endpoint types

A small rich dataset

A nicer default theme for ggplot2

pred_correction_core

Core prediction correction function

triangle_to_full

Lower to full triangle

replace_list_elements

Replace list elements by name

Read in VPC data

Simulated RTTE data (1x)

NONMEM output table import function

Simulate PK data from a 1-compartment iv model

Create a customized VPC theme

standardize_column

Confirm that a column is in the data, and rename data to prepare that column for later use.

Empty ggplot2 theme

Simulated RTTE data (100x)

A collection of internal ggplot helpers for VPC plotting

VPC function for left- or right-censored data (e.g. BLOQ data)

VPC function for categorical

VPC function for time-to-event (survival) data

vpc: Create Visual Predictive Checks

check_stratification_columns_available

Check whether stratification columns are available

Create a vpcdb object, and standardize parameter checking

Calculate appropriate bin separators for vpc

calc_pred_corr_continuous

Perform prediction-correction

Compute Kaplan-Meier statistics

add_stratification

Adds stratification to data set

Function to bin data based on a vector of bin separators, e.g. for use in VPC

draw_params_mvr

Draw parameters from multivariate distribution

Check and standardize limits of quantification

Remove values that are not observed values from data

format_vpc_input_data

Prepare VPC data for future calculations by standardizing column names and modifying the input data based on the limits of quantification, stratification, and logarithmic values.

Compute KMMC statistics

create_vpc_theme

Create new vpc theme

Define bins for many types of data

define_data_columns

Define data column defaults for various softwares