aqrVPC {nlmeVPC} | R Documentation |
This function draws the visual predictive check (VPC) plot using additive quantile regression. The quantile regression methods are used to calculate quantiles.
aqrVPC(orig_data,
sim_data,
probs = c(0.1,0.5,0.9),
conf.level = 0.95,
X_name = "TIME",
Y_name = "DV",
MissingDV = NULL,
plot_caption = TRUE,
DV_point = TRUE,
plot_flag = TRUE,
linesize = 0.7,
pointsize = 0.7,
captionsize = 10,
qss_lambda = NULL, ...)
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. |
probs |
A numeric vector of probabilities. |
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). |
MissingDV |
Name of missing indicator variable in orig_data, which have value 1 if missing, value 0 otherwise. (usually "MDV" in pharmacokinetic data). |
plot_caption |
Put caption with additional information if TRUE; omit if FALSE. |
DV_point |
Draw point (X, Y) in the plot 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. |
captionsize |
Size of caption. |
qss_lambda |
Smoothing parameter in quantreg::qss function. Larger lambda produces a smoother fit. |
... |
Arguments to be passed to methods. |
aqrVPC plot or the values to draw aqrVPC plot.
Koenker, Roger, and Kevin F. Hallock. "Quantile regression." Journal of economic perspectives 15.4 (2001): 143-156.
Jamsen, K. M., Patel, K., Nieforth, K., & Kirkpatrick, C. M. (2018). A regression approach to visual predictive checks for population pharmacometric models. CPT: pharmacometrics & systems pharmacology, 7(10), 678-686.
data(origdata)
data(simdata)
aqrVPC(origdata,simdata)