PopED (version 0.7.0)

feps.add: RUV model: Additive .

Description

This is a residual unexplained variability (RUV) model function that encodes the model described above. The function is suitable for input to the create.poped.database function using the fError_file argument.

Usage

feps.add(model_switch, xt, parameters, epsi, poped.db)

Value

A list consisting of:

1. y the values of the model at the specified points.

2. poped.db A (potentially modified) poped database.

Arguments

model_switch

a vector of values, the same size as xt, identifying which model response should be computed for the corresponding xt value. Used for multiple response models.

xt

a vector of independent variable values (often time).

parameters

A named list of parameter values.

epsi

A matrix with the same number of rows as the xt vector, columns match the numbers defined in this function.

poped.db

a poped database. This can be used to extract information that may be needed in the model file.

See Also

Other models: feps.add.prop(), feps.prop(), ff.PK.1.comp.oral.md.CL(), 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 RUV_models: feps.add.prop(), feps.prop()

Examples

library(PopED)

## find the parameters that are needed to define from the structural model
ff.PK.1.comp.oral.sd.KE

## -- parameter definition function 
## -- names match parameters in function ff
sfg <- function(x,a,bpop,b,bocc){
  parameters=c(KE=bpop[1]*exp(b[1]),
               V=bpop[2]*exp(b[2]),
               KA=bpop[3]*exp(b[3]),
               Favail=bpop[4],
               DOSE=a[1])
  return(parameters) 
}

## -- Define initial design  and design space
poped.db <- create.poped.database(ff_fun=ff.PK.1.comp.oral.sd.KE,
                                  fg_fun=sfg,
                                  fError_fun=feps.add,
                                  bpop=c(KE=0.15/8, V=8, KA=1.0, Favail=1), 
                                  notfixed_bpop=c(1,1,1,0),
                                  d=c(KE=0.07, V=0.02, KA=0.6), 
                                  sigma=1,
                                  groupsize=32,
                                  xt=c( 0.5,1,2,6,24,36,72,120),
                                  minxt=0,
                                  maxxt=120,
                                  a=70)

##  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)