The input data set (data_set) is a data frame that specifies
observations, model events, and / or parameter values for a population
of individuals.
data_set(x, data, ...)# S4 method for mrgmod,data.frame
data_set(
  x,
  data,
  .subset = TRUE,
  .select = TRUE,
  object = NULL,
  need = NULL,
  ...
)
# S4 method for mrgmod,ANY
data_set(x, data, ...)
# S4 method for mrgmod,ev
data_set(x, data, ...)
# S4 method for mrgmod,missing
data_set(x, object, ...)
model object
data set
passed along
an unquoted expression passed to 
dplyr::filter; retain only certain rows in the data set
passed to dplyr::select; retain only certain 
columns in the data set; this should be the result of a call to 
dplyr::vars()
character name of an object existing in $ENV 
to use for the data set
passed to inventory
Input data sets are R data frames that can include columns 
with any valid name, however columns with selected names are 
treated specially by mrgsolve and incorporated into the 
simulation.
ID specifies the subject ID and is required for every 
input data set.
When columns have the same name as parameters ($PARAM in 
the model specification file), the values in those columns will 
be used to update the corresponding parameter as the simulation 
progresses.
Input data set may include the following columns related to 
PK dosing events: time, cmt, amt, rate,
ii, addl, ss.  Along with ID, time 
is a required column in the input data set unless $PRED is in 
use.  Upper case PK dosing column names including
TIME, CMT, AMT, RATE, II,
ADDL, SS are also recognized.  However, an 
error will be generated if a mix of upper case and lower
case columns in this family are found.
time is the observation or event time, cmt 
is the compartment number (see init), amt 
is the dosing amount, rate is the infusion rate, 
ii is the dosing interval, addl specifies 
additional doses to administer, and ss is a flag 
for steady state dosing.  These column names operate 
similarly to other non-linear mixed effects modeling 
software.
An error will be generated when mrgsolve detects that the data set
is not sorted by time within an individual.
Only numeric data can be brought in to the problem.  
Any non-numeric data columns will be dropped with warning.  
See numerics_only, which is used 
to prepare the data set.
An error will be generated if any parameter columns in the 
input data set contain NA.  Likewise, and error will 
be generated if missing values are found in the following
columns: ID, time/TIME, rate/RATE.
See exdatasets for different example data sets.
# NOT RUN {
mod <- mrgsolve::house()
data <- expand.ev(ID=seq(3), amt=c(10, 20))
mod %>% data_set(data, ID > 1) %>% mrgsim()
data(extran1)
head(extran1)
mod %>% data_set(extran1) %>% mrgsim()
mod %>% mrgsim(data = extran1)
# }
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