simulate,RuleDesign-method | R Documentation |
Simulate outcomes from a rule-based design
## S4 method for signature 'RuleDesign'
simulate(
object,
nsim = 1L,
seed = NULL,
truth,
args = NULL,
parallel = FALSE,
nCores = min(parallel::detectCores(), 5L),
...
)
object |
the |
nsim |
the number of simulations (default: 1) |
seed |
see |
truth |
a function which takes as input a dose (vector) and returns the
true probability (vector) for toxicity. Additional arguments can be supplied
in |
args |
data frame with arguments for the |
parallel |
should the simulation runs be parallelized across the clusters of the computer? (not default) |
nCores |
how many cores should be used for parallel computing? Defaults to the number of cores on the machine, maximum 5. |
... |
not used |
an object of class GeneralSimulations
# nolint start
# Define the dose-grid
emptydata <- Data(doseGrid = c(5, 10, 15, 25, 35, 50, 80))
# inizialing a 3+3 design with constant cohort size of 3 and
# starting dose equal 5
myDesign <- RuleDesign(
nextBest = NextBestThreePlusThree(),
cohort_size = CohortSizeConst(size = 3L),
data = emptydata,
startingDose = 5
)
model <- LogisticLogNormal(
mean = c(-0.85, 1),
cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
ref_dose = 50
)
## define the true function
myTruth <- probFunction(model, alpha0 = 7, alpha1 = 8)
# Perform the simulation
## For illustration purpose only 10 simulation is produced (nsim=10).
threeSims <- simulate(myDesign,
nsim = 10,
seed = 35,
truth = myTruth,
parallel = FALSE
)
# nolint end
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