View source: R/poped_optim_3.R
poped_optim_3 | R Documentation |
Optimize the objective function. The function works for both discrete and
continuous optimization variables. If more than one optimization method is
specified then the methods are run in series. If loop_methods=TRUE
then the series of optimization methods will be run for iter_max
iterations, or until the efficiency of the design after the current series
(compared to the start of the series) is less than stop_crit_eff
.
poped_optim_3(
poped.db,
opt_xt = poped.db$settings$optsw[2],
opt_a = poped.db$settings$optsw[4],
opt_x = poped.db$settings$optsw[3],
opt_samps = poped.db$settings$optsw[1],
opt_inds = poped.db$settings$optsw[5],
method = c("ARS", "BFGS", "LS"),
control = list(),
trace = TRUE,
fim.calc.type = poped.db$settings$iFIMCalculationType,
ofv_calc_type = poped.db$settings$ofv_calc_type,
ds_index = poped.db$parameters$ds_index,
approx_type = poped.db$settings$iApproximationMethod,
d_switch = poped.db$settings$d_switch,
ED_samp_size = poped.db$settings$ED_samp_size,
bLHS = poped.db$settings$bLHS,
use_laplace = poped.db$settings$iEDCalculationType,
out_file = "",
parallel = F,
parallel_type = NULL,
num_cores = NULL,
loop_methods = ifelse(length(method) > 1, TRUE, FALSE),
iter_max = 10,
stop_crit_eff = 1.001,
stop_crit_diff = NULL,
stop_crit_rel = NULL,
ofv_fun = poped.db$settings$ofv_fun,
maximize = T,
allow_replicates = TRUE,
allow_replicates_xt = TRUE,
allow_replicates_a = TRUE,
...
)
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? |
opt_samps |
Are the number of sample times per group being optimized? |
opt_inds |
Are the number of individuals per group being optimized? |
method |
A vector of optimization methods to use in a sequential
fashion. Options are |
control |
Contains control arguments specified for each method separately. |
trace |
Should the algorithm output results intermittently. |
fim.calc.type |
The method used for calculating the FIM. Potential values:
|
ofv_calc_type |
OFV calculation type for FIM
|
ds_index |
Ds_index is a vector set to 1 if a parameter is uninteresting, otherwise 0.
size=(1,num unfixed parameters). First unfixed bpop, then unfixed d, then unfixed docc and last unfixed sigma.
Default is the fixed effects being important, everything else not important. Used in conjunction with
|
approx_type |
Approximation method for model, 0=FO, 1=FOCE, 2=FOCEI, 3=FOI. |
d_switch |
D-family design (1) or ED-family design (0) (with or without parameter uncertainty) |
ED_samp_size |
Sample size for E-family sampling |
bLHS |
How to sample from distributions in E-family calculations. 0=Random Sampling, 1=LatinHyperCube – |
use_laplace |
Should the Laplace method be used in calculating the expectation of the OFV? |
out_file |
Save output from the optimization to a file. |
parallel |
Should we use parallel computations? |
parallel_type |
Which type of parallelization should be used?
Can be "snow" or "multicore". "snow" works on Linux-like systems & Windows. "multicore" works only on
Linux-like systems. By default this is chosen for you depending on your operating system.
See |
num_cores |
The number of cores to use in the parallelization. By default is set to the number
output from
|
loop_methods |
Should the optimization methods be looped for
|
iter_max |
If line search is used then the algorithm tests if line
search (always run at the end of the optimization iteration) changes the
design in any way. If not, the algorithm stops. If yes, then a new
iteration is run unless |
stop_crit_eff |
If |
stop_crit_diff |
If |
stop_crit_rel |
If |
ofv_fun |
User defined function used to compute the objective function. The function must have a poped database object as its first argument and have "..." in its argument list. Can be referenced as a function or as a file name where the function defined in the file has the same name as the file. e.g. "cost.txt" has a function named "cost" in it. |
maximize |
Should the objective function be maximized or minimized? |
allow_replicates |
Should the algorithm allow parameters to have the same value? |
... |
arguments passed to other functions. |
This function takes information from the PopED database supplied as an argument. The PopED database supplies information about the the model, parameters, design and methods to use. Some of the arguments coming from the PopED database can be overwritten; if they are supplied then they are used instead of the arguments from the PopED database.
M. Foracchia, A.C. Hooker, P. Vicini and A. Ruggeri, "PopED, a software fir optimal experimental design in population kinetics", Computer Methods and Programs in Biomedicine, 74, 2004.
J. Nyberg, S. Ueckert, E.A. Stroemberg, S. Hennig, M.O. Karlsson and A.C. Hooker, "PopED: An extended, parallelized, nonlinear mixed effects models optimal design tool", Computer Methods and Programs in Biomedicine, 108, 2012.
Other Optimize:
Doptim()
,
LEDoptim()
,
RS_opt()
,
a_line_search()
,
bfgsb_min()
,
calc_autofocus()
,
calc_ofv_and_grad()
,
mfea()
,
optim_ARS()
,
optim_LS()
,
poped_optim()
,
poped_optim_1()
,
poped_optim_2()
,
poped_optimize()
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