Computes the exponential p-value weights for multiple testing.
Given estimated means
mu of test statistics
the p-value weights are proportional to
for a tilt parameter
beta. In addition, the large weights are truncated
at a maximum value
UB (upper bound), and the remaining weight is re-distributed
among the rest of the statistics.
the estimated means of the test statistics
(optional) weights are proportional to
(optional) upper bound on the weights (default
Specifically, it is assumed that
T are Gaussian with mean
mu. One-sided tests of
are conducted using the test statistics
T. To optimize power,
different levels are allocated to different tests.
For more details, see the paper "Optimal Multiple Testing Under a
Gaussian Prior on the Effect Sizes", by Dobriban, Fortney, Kim and Owen,
The exponential weights.
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