mftot | R Documentation |
Compute the FIM given specific model(s), parameters, design and methods.
mftot(
model_switch,
groupsize,
ni,
xt,
x,
a,
bpop,
d,
sigma,
docc,
poped.db,
...
)
model_switch |
A matrix that is the same size as xt, specifying which model each sample belongs to. |
groupsize |
A vector of the number of individuals in each group. |
ni |
A vector of the number of samples in each group. |
xt |
A matrix of sample times. Each row is a vector of sample times for a group. |
x |
A matrix for the discrete design variables. Each row is a group. |
a |
A matrix of covariates. Each row is a group. |
bpop |
The fixed effects parameter values. Supplied as a vector. |
d |
A between subject variability matrix (OMEGA in NONMEM). |
sigma |
A residual unexplained variability matrix (SIGMA in NONMEM). |
docc |
A between occasion variability matrix. |
poped.db |
A PopED database. |
As a list:
ret |
The FIM |
poped.db |
A PopED database |
For an easier function to use, please see evaluate.fim
.
Other FIM:
LinMatrixH()
,
LinMatrixLH()
,
LinMatrixL_occ()
,
calc_ofv_and_fim()
,
ed_laplace_ofv()
,
ed_mftot()
,
efficiency()
,
evaluate.e.ofv.fim()
,
evaluate.fim()
,
gradf_eps()
,
mf3()
,
mf7()
,
ofv_criterion()
,
ofv_fim()
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)
#####################################
mftot(model_switch=poped.db$design$model_switch,
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,
bpop=poped.db$parameters$param.pt.val$bpop,
d=poped.db$parameters$param.pt.val$d,
sigma=poped.db$parameters$sigma,
docc=poped.db$parameters$param.pt.val$docc,
poped.db)["ret"]
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