Repeat each design row the specified number of times. This is primarily used
for cluster computing where jobs are distributed with batches of replications
and later aggregated into a complete simulation object
(see runArraySimulation and SimCollect).
expandDesign(Design, repeat_conditions)object created by createDesign which should have
its rows repeated for optimal HPC schedulers
integer vector used to repeat each design row the specified number of times. Can either be a single integer, which repeats each row this many times, or an integer vector equal to the number of total rows in the created object.
This argument is useful when distributing independent row conditions to
cluster computing environments, particularly with different replication
information. For example, if 1000 replications in total are the target but
the condition is repeated over 4 rows then only 250 replications per row
would be required across the repeated conditions. See
SimCollect for combining the simulation objects
once complete
a tibble or data.frame containing the simulation experiment
conditions to be evaluated in runSimulation
Chalmers, R. P., & Adkins, M. C. (2020). Writing Effective and Reliable Monte Carlo Simulations
with the SimDesign Package. The Quantitative Methods for Psychology, 16(4), 248-280.
doi:10.20982/tqmp.16.4.p248
Sigal, M. J., & Chalmers, R. P. (2016). Play it again: Teaching statistics with Monte
Carlo simulation. Journal of Statistics Education, 24(3), 136-156.
doi:10.1080/10691898.2016.1246953
if (FALSE) { # \dontrun{
# repeat each row 4 times (for cluster computing)
Design <- createDesign(N = c(10, 20),
SD.equal = c(TRUE, FALSE))
Design4 <- expandDesign(Design, 4)
Design4
# repeat first two rows 2x and the rest 4 times (for cluster computing
# where first two conditions are faster to execute)
Design <- createDesign(SD.equal = c(TRUE, FALSE),
N = c(10, 100, 1000))
Design24 <- expandDesign(Design, c(2,2,rep(4, 4)))
Design24
} # }