computeFinalTest {REMixed} | R Documentation |
Compute final estimation
Description
Computes a final saem and wald test if 'test' on the final model found by remix algorithm.
Usage
computeFinalTest(
remix.output,
dynFUN,
y,
ObsModel.transfo,
final.project = NULL,
pop.set = NULL,
prune = NULL,
n = NULL,
parallel = TRUE,
ncores = NULL,
print = TRUE,
digits = 3,
trueValue = NULL,
test = TRUE,
p.max = 0.05
)
Arguments
remix.output |
a |
dynFUN |
function computing the dynamics of interest for a set of parameters. This function need to contain every sub-function that it may needs (as it is called in a
See |
y |
initial condition of the mechanism model, conform to what is asked in dynFUN. |
ObsModel.transfo |
list containing two lists of transformations and two vectors linking each transformations to their observation model name in the Monolix project. The list should include identity transformations and be named Both
|
final.project |
directory of the final Monolix project (default add "_upd" to the Monolix project). |
pop.set |
population parameters setting for final estimation (see details). |
prune |
percentage for prunning ( |
n |
number of points for gaussian quadrature (see |
parallel |
logical, if the computation should be done in parallel when possible (default TRUE). |
ncores |
number of cores for parallelization (default NULL and |
print |
logical, if the results and algotihm steps should be displayed in the console (default to TRUE). |
digits |
number of digits to print (default to 3). |
trueValue |
-for simulation purposes- named vector of true value for parameters. |
test |
if Wald test should be computed at the end of the iteration. |
p.max |
maximum value to each for wald test p.value (default 0.05). |
Details
For population parameter estimation settings, see (<https://monolixsuite.slp-software.com/r-functions/2024R1/setpopulationparameterestimationsettings>).
Value
a remix object on which final SAEM and test, if test
is TRUE
, have been computed.
Examples
## Not run:
project <- getMLXdir()
ObsModel.transfo = list(S=list(AB=log10),
linkS="yAB",
R=rep(list(S=function(x){x}),5),
linkR = paste0("yG",1:5))
alpha=list(alpha0=NULL,
alpha1=setNames(paste0("alpha_1",1:5),paste0("yG",1:5)))
y = c(S=5,AB=1000)
res = cv.remix(project = project,
dynFUN = dynFUN_demo,
y = y,
ObsModel.transfo = ObsModel.transfo,
alpha = alpha,
selfInit = TRUE,
eps1=10**(-2),
ncores=8,
nlambda=8,
eps2=1)
res_with_test = computeFinalTest(retrieveBest(res0,criterion=BICc),
dynFUN_demo,
y,
ObsModel.transfo)
## End(Not run)