PopED (version 0.1.0)

blockheader_2: Header function for optimization routines

Description

Create some output to the screen and a text file that summarizes the problem you are tying to solve.

Usage

blockheader_2(name, iter, poped.db, e_flag = FALSE,
  opt_xt = poped.db$optsw[2], opt_a = poped.db$optsw[4],
  opt_x = poped.db$optsw[4], opt_samps = poped.db$optsw[1],
  opt_inds = poped.db$optsw[5], fmf = 0, dmf = 0, bpop = NULL,
  d = NULL, docc = NULL, sigma = NULL,
  name_header = poped.db$strOutputFileName,
  file_path = poped.db$strOutputFilePath, ...)

Arguments

name

The name used for the output file. Combined with name_header and iter. If "" then output is to the screen.

iter

The last number in the name printed to the output file, combined with name.

name_header

The initial portion of the file name.

file_path

The path to where the file should be created.

...

Additional arguments passed to further functions.

poped.db

A PopED database.

opt_xt

Should the sample times be optimized?

opt_a

Should the continuous design variables be optimized?

opt_x

Should the discrete design variables be optimized?

fmf

The initial value of the FIM. If set to zero then it is computed.

dmf

The inital OFV. If set to zero then it is computed.

e_flag

Shuould output be with uncertainty around parameters?

opt_samps

Are the nuber of sample times per group being optimized?

opt_inds

Are the nuber of individuals per group being optimized?

bpop

Matrix defining the fixed effects, per row (row number = parameter_number) we should have:

• column 1 the type of the distribution for E-family designs (0 = Fixed, 1 = Normal, 2 = Uniform, 3 = User Defined Distribution, 4 = lognormal and 5 = t

d

Matrix defining the diagnonals of the IIV (same logic as for the fixed efects). can also just supply the parameter values as a c().

docc

Matrix defining the IOV, the IOV variances and the IOV distribution

sigma

Matrix defining the variances can covariances of the residual variability terms of the model. can also just supply the diagnonal parameter values (variances) as a c().

Value

• fn A file handle (or '' if name='')

See Also

Other Helper: blockexp; blockfinal_2; blockopt_2

Examples

## Warfarin example from software comparison in:
## Nyberg et al., "Methods and software tools for design evaluation 
##   for population pharmacokinetics-pharmacodynamics studies", 
##   Br. J. Clin. Pharm., 2014. 

## Optimization using an additive + proportional reidual error to 
##   avoid sample times at very low concentrations (time 0 or very late samoples).
library(PopED)

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

## -- parameter definition function 
## -- names match parameters in function ff
sfg <- function(x,a,bpop,b,bocc){
  parameters=c(CL=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_file="ff.PK.1.comp.oral.sd.CL",
                                  fg_file="sfg",
                                  fError_file="feps.add.prop",
                                  bpop=c(CL=0.15, V=8, KA=1.0, Favail=1), 
                                  notfixed_bpop=c(1,1,1,0),
                                  d=c(CL=0.07, V=0.02, KA=0.6), 
                                  sigma=c(0.01,0.25),
                                  groupsize=32,
                                  xt=c( 0.5,1,2,6,24,36,72,120),
                                  minxt=0,
                                  maxxt=120,
                                  a=70,
                                  mina=0,
                                  maxa=100)
# warfarin optimization model 


FIM <- evaluate.fim(poped.db) 
dmf <- det(FIM)

blockheader_2(name="",iter=1,poped.db)


blockheader_2(name='',
              iter=1,
              poped.db,
              e_flag=FALSE,
              opt_xt=TRUE,
              opt_a=TRUE,opt_x=poped.db$optsw[4],
              opt_samps=poped.db$optsw[1],opt_inds=poped.db$optsw[5],
              fmf=FIM,dmf=dmf,
              bpop=poped.db$param.pt.val$bpop,
              d=poped.db$param.pt.val$d,
              docc=poped.db$docc,sigma=poped.db$param.pt.val$sigma)