poso_simu_pop {posologyr} | R Documentation |
Estimate the prior distribution of population parameters
Description
Estimates the prior distribution of population parameters by Monte Carlo simulations
Usage
poso_simu_pop(
dat = NULL,
prior_model = NULL,
n_simul = 1000,
return_model = TRUE
)
Arguments
dat |
Dataframe. An individual subject dataset following the structure of NONMEM/rxode2 event records. |
prior_model |
A |
n_simul |
An integer, the number of simulations to be run. For |
return_model |
A boolean. Returns a rxode2 model using the simulated
ETAs if set to |
Value
If return_model
is set to FALSE
, a list of one element: a
dataframe $eta
of the individual values of ETA.
If return_model
is set to TRUE
, a list of the dataframe of the
individual values of ETA, and a rxode2 model using the simulated ETAs.
Examples
# model
mod_run001 <- function() {
ini({
THETA_Cl <- 4.0
THETA_Vc <- 70.0
THETA_Ka <- 1.0
ETA_Cl ~ 0.2
ETA_Vc ~ 0.2
ETA_Ka ~ 0.2
prop.sd <- sqrt(0.05)
})
model({
TVCl <- THETA_Cl
TVVc <- THETA_Vc
TVKa <- THETA_Ka
Cl <- TVCl*exp(ETA_Cl)
Vc <- TVVc*exp(ETA_Vc)
Ka <- TVKa*exp(ETA_Ka)
K20 <- Cl/Vc
Cc <- centr/Vc
d/dt(depot) = -Ka*depot
d/dt(centr) = Ka*depot - K20*centr
Cc ~ prop(prop.sd)
})
}
# df_patient01: event table for Patient01, following a 30 minutes intravenous
# infusion
df_patient01 <- data.frame(ID=1,
TIME=c(0.0,1.0,14.0),
DV=c(NA,25.0,5.5),
AMT=c(2000,0,0),
EVID=c(1,0,0),
DUR=c(0.5,NA,NA))
# estimate the prior distribution of population parameters
poso_simu_pop(dat=df_patient01,prior_model=mod_run001,n_simul=100)
[Package posologyr version 1.2.7 Index]