Individual Bayesian posterior predictions at short intervalsSource:
Contains the Bayesian posterior predictions at short intervals specified as an argument to the $run method of PM_fit. Default is every 12 minutes.
Contains the results of makePost, which is a
data frame with Bayesian posterior predicted outputs for all subjects.
To provide a more traditional experience in R,
the data frame is separated by columns into fields, e.g.
allows you to access them in an S3 way, e.g.
run1 is a
However, if you wish to manipulate the entire data frame,
data field, e.g.
trough <- run1$post$data %>% filter(time == 24). If
you are unfamiliar with the
%>% pipe function, please type
into the R console and look online for instructions/tutorials in tidyverse, a
powerful approach to data manipulation upon which Pmetrics is built.
Time of predictions in decimal hours
Prediction based on mean or median of Bayesian posterior parameter distribution
Output equation number
Predicted output for each outeq
Observation blocks within subjects as defined by EVID=4 dosing events
A data frame combining all the above fields as its columns
Create new object populated with Bayesian posterior predicted data at regular, frequent intervals
The parsed output from makePost.
Arguments passed to makeAUC
The object to use for AUC calculation