Contains the population predictions at short intervals specified as an argument to the run method of PM_fit. Default is every 12 minutes.
Details
#' The PM_pop object is both a data field within a PM_result, and itself an R6 object comprising data fields and associated methods suitable for analysis and plotting of population predictions generated during the run.
Because PM_pop objects are automatically added to the PM_result at the end of a successful run, it is generally not necessary for users to generate PM_pop objects themselves.
The main results are contained in the $data field,
and it is this field which is passed to the $plot and $summary methods.
data frame with population predicted outputs for all subjects.
To provide a more traditional experience in R,
the data frame is separated by columns into fields, e.g. id or time. This
allows you to access them in an S3 way, e.g. run1$pop$time if run1 is a
PM_result object.
However, if you wish to manipulate the entire data frame,
use the data field, e.g. trough <- run1$pop$data %>% filter(time == 24). If
you are unfamiliar with the %>% pipe function, please type help("%>%", "magrittr")
into the R console and look online for instructions/tutorials in tidyverse, a
powerful approach to data manipulation upon which Pmetrics is built.
Public fields
dataA data frame with the following columns:
id Subject id
time Time of predictions in decimal hours
icen Prediction based on mean or median of Bayesian posterior parameter distribution
outeq Output equation number
pred Predicted output for each outeq
block Observation blocks within subjects as defined by EVID=4 dosing events
Methods
Method new()
Create new object populated with population predicted data at regular, frequent intervals
Usage
PM_pop$new(PMdata = NULL, path = ".", ...)Method summary()
Summary method
Arguments
...Arguments passed to summary.PM_pop
Details
See summary.PM_pop.
Method auc()
Calculate AUC
Arguments
...Arguments passed to makeAUC
dataThe object to use for AUC calculation
Details
See makeAUC