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sims is an R package to generate datasets from JAGS or R code for use in simulation studies.
nlists ObjectsBy default, sims_simulate() returns the simulated
datasets in the form of an nlists object.
.rds FilesIf, however, save = TRUE then each nlist object is saved
as an .rds file in path.
set.seed(10)
sims_simulate("a <- runif(1)", nsims = 2L, save = TRUE, path = tempdir(), exists = NA)
#> [1] TRUE
sims_data_files(tempdir())
#> [1] "data0000001.rds" "data0000002.rds".rds FilesThe datasets in the .rds files can be imported as an
nlists object using sims_data().
.rds FilesThe values including the .Random.seed (not printed) that
were used to generate the datasets are saved in
.sims_args.rds which can be imported using
sims_info().
sims_info(tempdir())[1:5]
#> $code
#> [1] "a <- runif(1)"
#>
#> $constants
#> an nlist object with 0 numeric elements
#>
#> $parameters
#> an nlist object with 0 numeric elements
#>
#> $monitor
#> [1] "a"
#>
#> $nsims
#> [1] 2The fact that the arguments to sims_simulate() are saved
to file allows additional .rds datasets to be generated
using sims_add().
.rds FilesIf the user wishes to duplicate the datasets then they can either
regenerate them by specifying a different path but the same seed (using
set.seed()). Alternatively, they can copy the existing
.sims.rds and datasets files to a new directory using
sims_copy()
.rds FilesA user can check that all the datasets specified in
.sims.rds are present using sims_check().
Parallelization is implemented using the future package.
To use all available cores on the local machine simply execute the
following code before calling sims_simulate().
Progress is reported using the progressr package as follows.
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.
Health stats visible at Monitor.