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blockfinal.Rd
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/blockfinal.R
\name{blockfinal}
\alias{blockfinal}
\title{Result function for optimization routines}
\usage{
blockfinal(
fn,
fmf,
dmf,
groupsize,
ni,
xt,
x,
a,
model_switch,
bpop,
d,
docc,
sigma,
poped.db,
opt_xt = poped.db$settings$optsw[2],
opt_a = poped.db$settings$optsw[4],
opt_x = poped.db$settings$optsw[3],
opt_inds = poped.db$settings$optsw[5],
fmf_init = NULL,
dmf_init = NULL,
param_cvs_init = NULL,
compute_inv = TRUE,
out_file = NULL,
trflag = TRUE,
footer_flag = TRUE,
run_time = NULL,
...
)
}
\arguments{
\item{fn}{The file handle to write to.}
\item{fmf}{The initial value of the FIM. If set to zero then it is computed.}
\item{dmf}{The initial OFV. If set to zero then it is computed.}
\item{groupsize}{A vector of the number of individuals in each group.}
\item{ni}{A vector of the number of samples in each group.}
\item{xt}{A matrix of sample times. Each row is a vector of sample times for a group.}
\item{x}{A matrix for the discrete design variables. Each row is a group.}
\item{a}{A matrix of covariates. Each row is a group.}
\item{model_switch}{A matrix that is the same size as xt, specifying which model each sample belongs to.}
\item{bpop}{Matrix defining the fixed effects, per row (row number = parameter_number) we should have:
\itemize{
\item 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 = truncated normal)
\item column 2 defines the mean.
\item column 3 defines the variance of the distribution (or length of uniform distribution).
}
Can also just supply the parameter values as a vector \code{c()} if no uncertainty around the
parameter value is to be used. The parameter order of 'bpop' is defined in the 'fg_fun' or 'fg_file'. If you use named
arguments in 'bpop' then the order of this vector can be rearranged to match the 'fg_fun' or 'fg_file'.
See `reorder_parameter_vectors`.}
\item{d}{Matrix defining the diagonals of the IIV (same logic as for the fixed effects
matrix bpop to define uncertainty). One can also just supply the parameter values as a \code{c()}.
The parameter order of 'd' is defined in the 'fg_fun' or 'fg_file'. If you use named
arguments in 'd' then the order of this vector can be rearranged to match the 'fg_fun' or 'fg_file'.
See `reorder_parameter_vectors`.}
\item{docc}{Matrix defining the IOV, the IOV variances and the IOV distribution as for d and bpop.}
\item{sigma}{Matrix defining the variances can covariances of the residual variability terms of the model.
can also just supply the diagonal parameter values (variances) as a \code{c()}.}
\item{poped.db}{A PopED database.}
\item{opt_xt}{Should the sample times be optimized?}
\item{opt_a}{Should the continuous design variables be optimized?}
\item{opt_x}{Should the discrete design variables be optimized?}
\item{opt_inds}{Are the number of individuals per group being optimized?}
\item{fmf_init}{Initial FIM.}
\item{dmf_init}{Initial OFV.}
\item{param_cvs_init}{The initial design parameter RSE values in percent.}
\item{compute_inv}{should the inverse of the FIM be used to compute expected RSE values? Often not needed
except for diagnostic purposes.}
\item{out_file}{Which file should the output be directed to? A string, a file handle using
\code{\link{file}} or \code{""} will output to the screen.}
\item{trflag}{Should the optimization be output to the screen and to a file?}
\item{footer_flag}{Should the footer text be printed out?}
\item{...}{arguments passed to \code{\link{evaluate.fim}} and \code{\link{ofv_fim}}.}
}
\description{
Create some output to the screen and a text file that summarizes the problem you solved.
}
\examples{
library(PopED)
############# START #################
## Create PopED database
## (warfarin model for optimization)
#####################################
## 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 samples).
## 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_fun=ff.PK.1.comp.oral.sd.CL,
fg_fun=sfg,
fError_fun=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(prop=0.01,add=0.25),
groupsize=32,
xt=c( 0.5,1,2,6,24,36,72,120),
minxt=0.01,
maxxt=120,
a=c(DOSE=70),
mina=c(DOSE=0.01),
maxa=c(DOSE=100))
############# END ###################
## Create PopED database
## (warfarin model for optimization)
#####################################
FIM <- evaluate.fim(poped.db)
dmf <- det(FIM)
blockfinal(fn="",fmf=FIM,
dmf=dmf,
groupsize=poped.db$design$groupsize,
ni=poped.db$design$ni,
xt=poped.db$design$xt,
x=poped.db$design$x,a=poped.db$design$a,
model_switch=poped.db$design$model_switch,
poped.db$parameters$param.pt.val$bpop,
poped.db$parameters$param.pt.val$d,
poped.db$parameters$docc,
poped.db$parameters$param.pt.val$sigma,
poped.db,
opt_xt=TRUE,
fmf_init=FIM,
dmf_init=dmf,
param_cvs_init=get_rse(FIM,poped.db))
}
\seealso{
Other Helper:
\code{\link{blockexp}()},
\code{\link{blockheader}()},
\code{\link{blockopt}()}
}
\concept{Helper}
\keyword{internal}