| ff.PK.1.comp.oral.md.CL | R Documentation | 
This is a structural model function that encodes a  model that is 
one-compartment, oral absorption, multiple bolus dose, parameterized using CL.
The function is suitable for input to the create.poped.database function using the
ff_fun or ff_file argument.
ff.PK.1.comp.oral.md.CL(model_switch, xt, parameters, poped.db)
model_switch | 
 a vector of values, the same size as   | 
xt | 
 a vector of independent variable values (often time).  | 
parameters | 
 A named list of parameter values.  | 
poped.db | 
 a poped database. This can be used to extract information that may be needed in the model file.  | 
A list consisting of:
y the values of the model at the specified points.
poped.db A (potentially modified) poped database.
Other models: 
feps.add(),
feps.add.prop(),
feps.prop(),
ff.PK.1.comp.oral.md.KE(),
ff.PK.1.comp.oral.sd.CL(),
ff.PK.1.comp.oral.sd.KE(),
ff.PKPD.1.comp.oral.md.CL.imax(),
ff.PKPD.1.comp.sd.CL.emax()
Other structural_models: 
ff.PK.1.comp.oral.md.KE(),
ff.PK.1.comp.oral.sd.CL(),
ff.PK.1.comp.oral.sd.KE(),
ff.PKPD.1.comp.oral.md.CL.imax(),
ff.PKPD.1.comp.sd.CL.emax()
library(PopED)
## find the parameters that are needed to define in the structural model
ff.PK.1.comp.oral.md.CL
## -- parameter definition function 
## -- names match parameters in function ff
sfg <- function(x,a,bpop,b,bocc){
  parameters=c( V=bpop[1]*exp(b[1]),
                KA=bpop[2]*exp(b[2]),
                CL=bpop[3]*exp(b[3]),
                Favail=bpop[4],
                DOSE=a[1],
                TAU=a[2])
  return( parameters ) 
}
## -- Define design and design space
poped.db <- create.poped.database(ff_fun=ff.PK.1.comp.oral.md.CL,
                                  fg_fun=sfg,
                                  fError_fun=feps.add.prop,
                                  groupsize=20,
                                  m=2,
                                  sigma=c(0.04,5e-6),
                                  bpop=c(V=72.8,KA=0.25,CL=3.75,Favail=0.9), 
                                  d=c(V=0.09,KA=0.09,CL=0.25^2), 
                                  notfixed_bpop=c(1,1,1,0),
                                  notfixed_sigma=c(0,0),
                                  xt=c( 1,2,8,240,245),
                                  minxt=c(0,0,0,240,240),
                                  maxxt=c(10,10,10,248,248),
                                  a=cbind(c(20,40),c(24,24)),
                                  bUseGrouped_xt=1,
                                  maxa=c(200,24),
                                  mina=c(0,24))
##  create plot of model without variability 
plot_model_prediction(poped.db)
## evaluate initial design
FIM <- evaluate.fim(poped.db) 
FIM
det(FIM)
get_rse(FIM,poped.db)
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