bootVPC: The bootstrap visual predictive checks.

In nlmeVPC: Visual Model Checking for Nonlinear Mixed Effect Model

The bootstrap visual predictive checks.

Description

This function draws the visual predictive check plot with bootstrapped data. It compares the distribution of the simulated data to the distribution of the bootstrap samples that draw from the observed data. This plot reflects the uncertainty of the observed data and allows for more objective comparisons with the predicted median.

Usage

bootVPC(orig_data,
        sim_data,
        B = 1000,                  
        N_xbin = NULL,
        conf.level = 0.95,
        X_name = "TIME",
        Y_name = "DV",
        subject_name = "ID",                  
        MissingDV = NULL,
        DV_point = TRUE,                  
        plot_caption = TRUE,                  
        plot_flag = TRUE,
        linesize = 0.7,
        pointsize = 0.7,
        Kmethod = "cluster",                
        maxK = NULL,
        beta = 0.2,
        lambda = 0.3,
        R = 4,                
        C1 = 2.5,
        C2 = 7.8, ...)

Arguments

orig_data	A data frame of original data with X and Y variable.
sim_data	A matrix of simulated data with only Y values collected.
B	Number of bootstrap samples.
N_xbin	Number of bins in X variable. If NULL, optimal number of bins are automatically calcuated using optK function.
conf.level	Confidence level of the interval.
X_name	Name of X variable in orig_data (usually "TIME" in pharmacokinetic data).
Y_name	Name of Y variable in orig_data (usually "DV" in pharmacokinetic data).
subject_name	Name of subject variable in orig_data (usually "ID" in pharmacokinetic data).
MissingDV	Name of missing indicator variable in orig_data, which have value 1 if missing, value 0 otherwise. (usually "MDV" in pharmacokinetic data).
DV_point	Draw point (X, Y) in the plot if TRUE; omit if FALSE.
plot_caption	Put caption with additional information if TRUE; omit if FALSE.
plot_flag	Draw plot if TRUE; generate data for drawing plot if FALSE.
linesize	Size of line in the plot.
pointsize	Size of point in the plot.
Kmethod	The way to calculate the penalty in automatic binning."cluster" or "kernel".
maxK	The maximum number of bins.
beta	Additional parameter for automatic binning, used in optK function.
lambda	Additional parameter for automatic binning, used in optK function.
R	Additional parameter for automatic binning, used in optK function.
C1	Additional parameter for automatic binning, used in optK function.
C2	Additional parameter for automatic binning, used in optK function.
...	Arguments to be passed to methods.

Value

bootVPC plot or the values to draw bootVPC plot.

References

Post, T. M., et al. (2008) Extensions to the visual predictive check for facilitate model performance evaluation, Journal of pharmacokinetics and pharmacodynamics, 35(2), 185-202

Examples

data(origdata)
data(simdata)
bootVPC(origdata,simdata,N_xbin=8)

nlmeVPC documentation built on Dec. 28, 2022, 2:49 a.m.