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add_to_tid
environment
variable in run_on_cluster()
.summarize()
function to
calculate Monte Carlo standard errors and confidence intervals for all
inferential summary statistics. For summary statistics meant to estimate
a population quantity (e.g., the bias of an estimator), the Monte Carlo
standard error quantifies variability due to running a finite number of
simulation replicates.batch()
function, which allows for sharing of
data or objects between simulation replicates. Essentially, it allows
you to take your simulation replicates and divide them into “batches”;
all replicates in a given batch will then share a single set of objects.
The most common use case for this is if you have a simulation that
involves generating one dataset, analyzing it using multiple methods,
and then repeating this a number of times. See the documentation for
more info.summarize()
function and added several summary metrics
(correlation, covariance, n_reps); see the documentation for more
info.run_on_cluster()
.sessionInfo()
to
vars()
.sim_id
to rep_id
to avoid
confusion with sim_uid
.sim_uids
.keep_extra
option from
update_sim()
and update_sim_on_cluster()
..add
option from
set_levels()
.set_levels()
to prevent changing
of level variables once they are initially set.add_creator()
,
add_method()
, add_constants()
. Instead,
functions declared in the parent frame of the new_sim()
call are automatically added to the simulation object. It is now
recommended that simulation constants are stored and referenced in the
same way as levels; see “Advanced Usage” on the SimEngine website (https://avi-kenny.github.io/SimEngine/).add_method()
.set_config()
(since this was a source of
confusion among some users).These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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