Parallel test execution helper

Source: R/performance.R · Help: ?runHeteroTestsParallel

Executes a set of registered diagnostics in parallel when multiple CPU cores are available, falling back to sequential execution otherwise.

Usage

runHeteroTestsParallel(model, data, tests, n_cores = NULL)

Arguments

model

Fitted model object passed to each diagnostic. Must be compatible with the internal .test_factory registry.

data

Data frame used to fit model and supplied to each diagnostic.

tests

Character vector naming the diagnostics to execute.

n_cores

Optional positive integer giving the number of worker processes to spawn. Defaults to parallel::detectCores() - 1, with a lower bound of 1.

Value

Named list of test results in the order provided by tests.

Details

When n_cores exceeds one the diagnostics run on a socket cluster of that many workers (parallel::makeCluster()), started for the call, each of which loads the installed heteroTests. The model and the data travel to the workers with each task. With n_cores = 1, or when the default comes to one worker, the diagnostics run in the session.

Test i draws its random numbers from stream i of a L'Ecuyer-CMRG generator seeded by one draw from the session's generator, on the workers and in the session alike. A seeded call that runs a resampling test, such as "wild_bootstrap", therefore returns the same value each time and whatever n_cores, n_cores = 1 included. It is not the value that test returns when called directly from the same seed, which draws from the session's generator; both are bootstraps of the same data.

See also

cachedTest() for memoised execution of individual diagnostics.