View source: R/TestSet_LocalTest.R
TestSet_LocalTest | R Documentation |
Test a subset of hypotheses in its closure using a user-specified local test
TestSet_LocalTest( LocalTest, pvals, subset, alpha = 0.05, EarlyStop = FALSE, verbose = FALSE, mc.cores = 1L, chunksize = 4 * mc.cores, is.sorted = FALSE, ... ) TestSet_localTest( localTest, pvals, subset, alpha = 0.05, EarlyStop = FALSE, verbose = FALSE, mc.cores = 1L, chunksize = 4 * mc.cores, is.sorted = FALSE, ... )
LocalTest |
Function which defines a combination test. |
pvals |
Numeric vector of p-values. |
subset |
Numeric vector; the subset to be tested. |
alpha |
Numeric; the level to test at, if stopping early. Defaults to 0.05. |
EarlyStop |
Logical; set to TRUE to stop as soon as a hypothesis can be accepted at level alpha. This speeds up the procedure, but now only provides lower bounds on the p-values for the global test. |
verbose |
Logical; set to TRUE to print progress. |
mc.cores |
Number of cores to parallelize onto. |
chunksize |
Integer indicating the size of chunks to parallelize. E.g., if setting chunksize = mc.cores, each time a parallel computation is set up, each worker will perform only a single task. If mc.cores > chunksize, some threads will be inactive. |
is.sorted |
Logical, indicating whether the supplied p-values are already is.sorted. Defaults to FALSE. |
... |
Additional arguments. |
localTest |
A function specifying a local test (deprecated). |
The adjusted p-value for the test of the hypothesis that there are no false hypotheses among the selected subset.
## Simulate p-values; 10 from false hypotheses, 10 from true pvals = sort(c( rbeta(10, 1, 20), # Mean value of .1 runif(10) )) ## Test whether the highest 10 contain any false hypotheses using a Bonferroni test TestSet_LocalTest(function(x) { min(c(1, length(x) * min(x))) }, pvals, subset = 11:20)
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