| generate_model | R Documentation |
This function executes the make_model function provided by the user
and writes to file the resulting Model object(s). For example,
when simulating regression with a fixed design, X would be generated
in this function and n, p, beta, and sigma would
also be specified.
generate_model(object = ".", make_model, ..., seed = 123, vary_along = NULL)
object |
the name of the directory where directory named "files" exists
(or should be created) to save |
make_model |
a function that outputs an object of class
|
... |
optional parameters that may be passed to make_model |
seed |
an integer seed for the random number generator. |
vary_along |
character vector with all elements contained in names(...) See description for more details. |
When make_model has arguments, these can be passed using ....
These will be passed directly to make_model except for any arguments
named in vary_along. These arguments should be lists and a separate
model will be created for each combination of elements in these lists. For
example, if vary_along = c("n", "p"), then we can pass
n=as.list(c(50, 100, 150)) and p=as.list(c(10, 100)) and 6
models will be created, one for each pair of n and p. For each
pair (n,p), a distinct extension is added to the end of the model name. This
extension is generated using a hash function so that different values of the
vary_along parameters will lead to different model name extensions. This
ensures that if one later decides to add more values of the vary_along
parameters, this will not lead to pre-existing files being overwritten
(unless the same values of the vary_along combination are used again.
If object is a directory name, the function returns a reference or
list of references to the model(s) generated. If object is a
Simulation, then function returns the same Simulation object
but with references added to the new models created. These changes to the
Simulation object are saved to file.
make_model is called generating an object of class
Model, called model, which is saved to
dir/name/model.Rdata (where name is the name attribute of
model). This file also contains the random number generator state and
other information such as the function make_model itself and the date
when model was created.
new_model simulate_from_model
run_method
# initialize a new simulation
sim <- new_simulation(name = "normal-example",
label = "Normal Mean Estimation",
dir = tempdir())
# generate a model (and add it to the simulation)
sim <- generate_model(sim, make_my_example_model, n = 20)
# generate a sequence of models (and add them to the simulation)
sim <- generate_model(sim, make_my_example_model,
n = list(10, 20, 30),
vary_along = "n")
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